scientific essay meaning

Write Like a Scientist

A Guide to Scientific Communication

What is scientific writing ?

Scientific writing is a technical form of writing that is designed to communicate scientific information to other scientists. Depending on the specific scientific genre—a journal article, a scientific poster, or a research proposal, for example—some aspects of the writing may change, such as its purpose , audience , or organization . Many aspects of scientific writing, however, vary little across these writing genres. Important hallmarks of all scientific writing are summarized below. Genre-specific information is located here and under the “By Genre” tab at the top of the page.

What are some important hallmarks of professional scientific writing?

1. Its primary audience is other scientists. Because of its intended audience, student-oriented or general-audience details, definitions, and explanations — which are often necessary in lab manuals or reports — are not terribly useful. Explaining general-knowledge concepts or how routine procedures were performed actually tends to obstruct clarity, make the writing wordy, and detract from its professional tone.

2. It is concise and precise . A goal of scientific writing is to communicate scientific information clearly and concisely. Flowery, ambiguous, wordy, and redundant language run counter to the purpose of the writing.

3. It must be set within the context of other published work. Because science builds on and corrects itself over time, scientific writing must be situated in and reference the findings of previous work . This context serves variously as motivation for new work being proposed or the paper being written, as points of departure or congruence for new findings and interpretations, and as evidence of the authors’ knowledge and expertise in the field.

All of the information under “The Essentials” tab is intended to help you to build your knowledge and skills as a scientific writer regardless of the scientific discipline you are studying or the specific assignment you might be working on. In addition to discussions of audience and purpose , professional conventions like conciseness and specificity, and how to find and use literature references appropriately, we also provide guidelines for how to organize your writing and how to avoid some common mechanical errors .

If you’re new to this site or to professional scientific writing, we recommend navigating the sub-sections under “The Essentials” tab in the order they’re provided. Once you’ve covered these essentials, you might find information on genre- or discipline-specific writing useful.

Scientific Paper: What is it & How to Write it? (Steps and Format)

A white page, and a blinking cursor: How can a blank document be so intimidating? You might hear the voice of your Ph.D. professor rumbling in your head: “Well done with the research, why don’t you put all that data together in a scientific paper so we can get it published?”

Well, it’s more challenging than it sounds!

For first-time authors, the chances of writing their own scientific research may both be overwhelming and exciting. Encountered with a mountain of notes, data, remnants of the research process, and days spent doing experiments, it may be daunting to figure out where and how to begin the process of writing a scientific paper!

The good news is, you don’t have to be a talented writer to pen-down a good scientific paper, but just have to be an organized and careful writer.

This is why we have put time and effort into creating an exceptional guide on how to write a scientific paper that will help you present your research successfully to your supervisors or publications without any clutter!

Before we begin, let’s learn about the touchstones or benchmarks of scientific writing for authors!

What is a Scientific Paper? (Definition)

A scientific paper is a manuscript that represents an original work of scientific research or study. It can be an addition to the ongoing study in a field, can be groundbreaking, or a comparative study between different approaches.

Most times, a scientific paper draws the research performed by an individual or a group of people. These papers showcase valuable analysis in fields like theoretical physics, mathematics, etc., and are routinely published in scientific journals.

Read more: The Ultimate Guide on Technical Documentation

3 Golden Rules of Scientific Writing

According to a study by lijunsun, scientists and writers have identified difficulties in communicating science to the public through typical scientific prose.

Simply put, it is important for researchers to maintain a balance between receiving respect and recognition for their research in a particular field and making sure that their work is understandable to a wider audience. The latter can be achieved through clarity, simplicity, and accuracy.

Clarity – Research is unambiguous and free of irrelevant conjecture or detail.

Simplicity – Language, sentence, and paragraph structure are easy to comprehend and follow without losing scientific credibility or authority.

Accuracy – Data, figures, tables, references, and citations are illustrated verifiably and honestly.

Why are Scientific Papers Important?

A scientific paper is both a testing device and a teaching device.

When handled correctly, it empowers you to

Learn and read an assignment carefully,
Research the nuances of your topic,
Refine your focus to a strong,
Offer arguable thesis,
Select the best evidence to prove the analysis of your dissertation.

As a primary teaching device, the scientific paper in your field trains you to self-learn some rules and expectations in terms of:

Writing format,
Appropriateness of language and content,
Submission requirements,
Bibliographic styles, and much more.

As you move onward with your research, you’ll find that the scientific paper quickly becomes the educational “ coin of the realm .” Hence, it’s important to approach any scientific paper with zeal for higher learning.

Read more: Technical Report: What is it & How to Write it? (Steps & Structure Included)

How to Write a Scientific Paper? (Steps & Format)

When you begin with writing your scientific manuscript, the first thing to consider is the format and order of sections in relation to your research or the information you want to showcase.

A scientific paper follows the conventional format of research-based writing, which provides a deeper understanding of the purpose of each section. The structure starts with:

Step 1. Add Title in the Paper

A title should be of the fewest words possible, accurately describing the content of the paper. Try to eliminate unnecessary words such as “Investigations of …”, “A study of …”, “Observations on …”, etc.

An improperly titled scientific paper might never reach the readers for which it was intended. Hence, mention the name of the study, a particular region it was conducted in, or an element it contains in the title.

Step 2. Mention Keywords List

A keyword list offers the opportunity to add keywords, in addition to those already written in the title. Optimal use of keywords may increase the chances of interested parties to easily locate your scientific paper.

Step 3. Add Abstract

A well-defined abstract allows the reader to identify the basic content of your paper quickly and accurately, to determine its relevance, and decide whether to read it in its entirety. The abstract briefly states the principal, scope, and objectives of the research. The abstract typically should not exceed 250 words. If you can convey the important details of the paper in 100 words, do not try to use more.

Step 4. Start with Introduction

An introduction begins by introducing the authors and their relevant fields to the reader. A common mistake made is introducing their areas of study while not mentioning their major findings in descriptive scientific writing, enabling the reader to place the current work in context.

The ending of the introduction can be done through a statement of objectives or, with a brief statement of the principal findings. Either way, the reader must have an idea of where the paper is headed to process the development of the evidence.

Step 5. Mention Scientific Materials and Methods Used

The primary purpose of the ‘Materials and Methods’ section is to provide enough detail for a competent worker to replicate your research and reproduce the results.

The scientific method requires your results to be reproducible, and provide a basis for the reiteration of the study by others. However, if case your material and method have been previously published in a journal, only the name of the study and a literature reference is needed.

Step 6. Write down Results

Results display your findings, figures, and tables of your study. It represents the data, condensed, and digested with important trends that are extracted while researching. Since the results hold new knowledge that you are contributing to the world, it is important that your data is simply and clearly stated.

Step 7. Create a Discussion Section

A discussion involves talking and answering about different aspects of the scientific paper such as: what principles have been established or reinforced; how your findings compare to the findings of others, what generalizations can be drawn, and whether there are any practical/theoretical implications of your research.

Step 8. Mention References

A list of references presented alphabetically by author’s surname, or number, based on the publication, must be provided at the end of your scientific paper. The reference list must contain all references cited in the text. Include author details such as the title of the article, year of publication, name of journal or book or volume, and page numbers with each reference

Now that you know the key elements to include in your scientific paper, it’s time to introduce you to an awesome tool that will make writing a scientific paper, a breeze!

Ditch Your Boring, Old Editor, and Write a Scientific Paper the Smart Way with Bit.ai

Bit.ai is a new-age documentation and knowledge management tool that allows researchers and teams to collaborate, share, track, and manage all knowledge and research in one place. Bit documents, unlike your standard Word Docs or Google Docs, are interactive . This means that authors can use Bit to create interactive, media-rich scientific papers easily!

Bit.ai: Documentation tool for creating scientific papers

Thus, Bit brings together everything you need to conduct and write a comprehensive scientific paper under one roof, cutting down your efforts in half! Bit has a super easy and fun interface, making onboarding new users easier than ever!

All-in-all Bit is like Google Docs on steroids ! So, no more settling for those boring text editors when you have an excessively robust solution to walk you through!

Organized workspaces and folders – Bit brings all your research in one place by allowing you to organize information in workspaces and folders. Workspaces can be created around projects, studies, departments, and fields. Everyone added to a workspace can access and collaborate on its content. Inside each workspace, you can create an unlimited number of wikis and access your content library.
Content library – Bit has a content library at the workspace level where you can store and share assets. You can save images, files, and content easily and can access it at any point.
Rich embed options – Bit.ai integrates with over 100+ web applications (Ex: YouTube, PDFs, LucidChart, Google Drive, etc.) to help you weave information in their wikis beyond just text and images.
Smart search – Bit has very robust search functionality that allows anyone to find information quickly. You can search for folders, files, documents, and content inside your documents across all of your workspaces.
Interlink documents – Bit allows authors to create unlimited documents and interlink them to create wikis that expand the knowledge base. Simply highlight the words and you have the option to create a new document.
Permission & sharing access – Bit supports features like document tracking, cloud upload, templates, document locking, document expiration, password protection, etc.

Our team at bit.ai has created a few awesome templates to make your research process more efficient. Make sure to check them out before you go, y our team might need them!

Case Study Template
Research Paper Template
Competitor Research Template
Brainstorming Template
SWOT Analysis Template
White Paper Template

Read More: How Bit.ai Can Help You Manage Your Academic Research?

Over to You!

Scientific papers are the medium through which scientists report their work to the world. Their professional reputation is based on how these papers are acknowledged by the scientific community.

No matter how great the actual experiment is, a poorly written scientific paper may negatively affect one’s professional honor, or worse, prevent the paper from being published at all. Therefore, it is extremely crucial to learn everything about writing a scientific paper.

There is no better tool than Bit to help you save time and energy required for the whole writing process. It’s time to make a mark in the scientific community by showcasing a well-crafted scientific paper with Bit. If you want any further assistance in presenting your research, let us know by tweeting us @bit_docs. Cheers!

Further reads:

How To Write A Research Paper?

Thesis Statement: Definition, Importance, Steps & Tips!

How To Write A Case Study (With Template)

How to Write an Insane White Paper that Gets High Engagement?

Request for Proposal (RFP): What is it & How to Write it? (Free Template)

9 Essential Writing Tips Every Writer Must Use!

7 shocking reasons to use vpn at work, business presentation: definition, steps to create & tips to remember, service contract: what is it and how to draft a perfect one, software development process: steps to follow, project report: what is it & how to write it, how to embed google sheets within your documents.

About Bit.ai

Bit.ai is the essential next-gen workplace and document collaboration platform. that helps teams share knowledge by connecting any type of digital content. With this intuitive, cloud-based solution, anyone can work visually and collaborate in real-time while creating internal notes, team projects, knowledge bases, client-facing content, and more.

The smartest online Google Docs and Word alternative, Bit.ai is used in over 100 countries by professionals everywhere, from IT teams creating internal documentation and knowledge bases, to sales and marketing teams sharing client materials and client portals.

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Tools & Methods

How to successfully write a scientific essay.

Posted by Cody Rhodes

If you are undertaking a course which relates to science, you are more or less apt to write an essay on science. You need to know how to write a science essay irrespective of whether your professor gives you a topic or you come up with one. Additionally, you need to have an end objective in mind. Writing a science essay necessitates that you produce an article which has all the details and facts about the subject matter and it ought to be to the point. Also, you need to know and understand that science essays are more or less different from other types of essays. They require you to be analytical and precise when answering questions. Hence, this can be quite challenging and tiresome. However, that should not deter you from learning how to write your paper. You can always inquire for pre-written research papers for sale from writing services like EssayZoo.

Also, you can read other people’s articles and find out how they produce and develop unique and high-quality papers. Moreover, this will help you understand how to approach your essays in different ways. Nonetheless, if you want to learn how to write a scientific paper in a successful manner, consider the following tips.

How to successfully write a scientific essay

Select a topic for your article Like any other type of essay, you need to have a topic before you start the actual writing process. Your professor or instructor may give you a science essay topic to write about or ask you to come up with yours. When selecting a topic for your paper, ensure that you choose one you can write about. Do not pick a complex topic which can make the writing process boring and infuriating for you. Instead, choose one that you are familiar with. Select a topic you will not struggle gathering information about. Also, you need to have an interest in it. If you are unable to come up with a good topic, trying reading other people’s articles. This will help you develop a topic with ease.

Draft a plan After selecting a topic, the next step is drafting a plan or an outline. An outline is fundamental in writing a scientific essay as it is the foundation on which your paper is built. Additionally, it acts as a road map for your article. Hence, you need to incorporate all the thoughts and ideas you will include in your essay in the outline. You need to know what you will include in the introduction, the body, and the conclusion. Drafting a plan helps you save a lot of time when writing your paper. Also, it helps you to keep track of the primary objective of your article.

Start writing the article After drafting a plan, you can begin the writing process. Writing your paper will be smooth and easier as you have an outline which helps simplify the writing process. When writing your article, begin with a strong hook for your introduction. Dictate the direction your paper will take. Provide some background information and state the issue you will discuss as well as the solutions you have come up with. Arrange the body of your article according to the essay structure you will use to guide you. Also, ensure that you use transitory sentences to show the relationship between the paragraphs of your article. Conclude your essay by summarizing all the key points. Also, highlight the practical potential of our findings and their impacts.

Proofread and check for errors in the paper Before submitting or forwarding your article, it is fundamental that you proofread and correct all the errors that you come across. Delivering a paper that is full of mistakes can affect your overall performance in a negative manner. Thus, it is essential you revise your paper and check for errors. Correct all of them. Ask a friend to proofread your paper. He or she may spot some of the mistakes you did not come across.

In conclusion, writing a scientific essay differs from writing other types of papers. A scientific essay requires you to produce an article which has all the information and facts about the subject matter and it ought to be to the point. Nonetheless, the scientific essay formats similar to the format of any other essay: introduction, body, and conclusion. You need to use your outline to guide you through the writing process. To learn how to write a scientific essay in a successful manner, consider the tips above.

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Definition and Examples of Science Writing

Glossary of Grammatical and Rhetorical Terms

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The term science writing refers to writing about a scientific subject matter, often in a non-technical manner for an audience of non-scientists (a form of journalism or creative nonfiction ). Also called popular science writing . (Definition No. 1)

Science writing may also refer to writing that reports scientific observations and results in a manner governed by specific conventions (a form of technical writing ). More commonly known as scientific writing . (Definition No. 2)

Examples and Observations

"Because science writing is intended to be entertaining enough to capture the continued interest of potential readers, its style is much less somber than the usual scientific writing [i.e., definition No. 2, above]. The use of slang , puns , and other word plays on the English language are accepted and even encouraged. . . . "Distinguishing between science writing and scientific writing is reasonable—they have different purposes and a different audience . However, one would be ill-advised to use the term 'science writing' or 'popular writing' in a disparaging way. Writing (or providing consultation for others who are writing) popularized accounts based on scientific research should be an important part of every scientists' outreach activities. The wider community is essential to adequate support for scientific endeavors."
An Example of Science Writing: "Stripped for Parts": "Sustaining a dead body until its organs can be harvested is a tricky process requiring the latest in medical technology. But it's also a distinct anachronism in an era when medicine is becoming less and less invasive. Fixing blocked coronary arteries, which not long ago required prying a patient's chest open with a saw and spreader, can now be accomplished with a tiny stent delivered to the heart on a slender wire threaded up the leg. Exploratory surgery has given way to robot cameras and high-resolution imaging. Already, we are eyeing the tantalizing summit of gene therapy, where diseases are cured even before they do damage. Compared with such microscale cures, transplants—which consist of salvaging entire organs from a heart-beating cadaver and sewing them into a different body—seem crudely mechanical, even medieval."

On Explaining Science

"The question is not "should" you explain a concept or process, but "how" can you do so in a way that is clear and so readable that it is simply part of the story?

"Use explanatory strategies such as ...

- "People who study what makes an explanation successful have found that while giving examples is helpful, giving nonexamples is even better. "Nonexamples are examples of what something is not . Often, that kind of example will help clarify what the thing is . If you were trying to explain groundwater, for instance, you might say that, while the term seems to suggest an actual body of water, such as a lake or an underground river, that would be an inaccurate image. Groundwater is not a body of water in the traditional sense; rather, as Katherine Rowan, communications professor, points out, it is water moving slowly but relentlessly through cracks and crevices in the ground below us... "Be acutely aware of your readers' beliefs. You might write that chance is the best explanation of a disease cluster; but this could be counterproductive if your readers reject chance as an explanation for anything. If you are aware that readers' beliefs may collide with an explanation you give, you may be able to write in a way that doesn't cause these readers to block their minds to the science you explain."

The Lighter Side of Science Writing

"In this paragraph I will state the main claim that the research makes, making appropriate use of ' scare quotes ' to ensure that it's clear that I have no opinion about this research whatsoever.

"In this paragraph, I will briefly (because no paragraph should be more than one line) state which existing scientific ideas this new research 'challenges.'

"If the research is about a potential cure or a solution to a problem, this paragraph will describe how it will raise hopes for a group of sufferers or victims.

"This paragraph elaborates on the claim, adding weasel-words like 'the scientists say' to shift responsibility for establishing the likely truth or accuracy of the research findings on to absolutely anybody else but me, the journalist. ..."

(Janice R. Matthews and Robert W. Matthews, Successful Scientific Writing: A Step-by-Step Guide for the Biological and Medical Sciences , 4th ed. Cambridge University Press, 2014)

(Jennifer Kahn, "Stripped for Parts." Wired. March 2003. Reprinted in The Best American Science Writing 2004 , edited by Dava Sobel. HarperCollins, 2004)

(Sharon Dunwoody, "On Explaining Science." A Field Guide for Science Writers , 2nd ed., ed. by Deborah Blum, Mary Knudson, and Robin Marantz Henig. Oxford University Press, 2006)

(Martin Robbins, "This Is a News Website Article About a Scientific Paper." The Guardian , September 27, 2010)

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Scientific Papers

Scientific papers are for sharing your own original research work with other scientists or for reviewing the research conducted by others. As such, they are critical to the evolution of modern science, in which the work of one scientist builds upon that of others. To reach their goal, papers must aim to inform, not impress. They must be highly readable — that is, clear, accurate, and concise. They are more likely to be cited by other scientists if they are helpful rather than cryptic or self-centered.

Scientific papers typically have two audiences: first, the referees, who help the journal editor decide whether a paper is suitable for publication; and second, the journal readers themselves, who may be more or less knowledgeable about the topic addressed in the paper. To be accepted by referees and cited by readers, papers must do more than simply present a chronological account of the research work. Rather, they must convince their audience that the research presented is important, valid, and relevant to other scientists in the same field. To this end, they must emphasize both the motivation for the work and the outcome of it, and they must include just enough evidence to establish the validity of this outcome.

Papers that report experimental work are often structured chronologically in five sections: first, Introduction ; then Materials and Methods , Results , and Discussion (together, these three sections make up the paper's body); and finally, Conclusion .

The Introduction section clarifies the motivation for the work presented and prepares readers for the structure of the paper.
The Materials and Methods section provides sufficient detail for other scientists to reproduce the experiments presented in the paper. In some journals, this information is placed in an appendix, because it is not what most readers want to know first.
The Results and Discussion sections present and discuss the research results, respectively. They are often usefully combined into one section, however, because readers can seldom make sense of results alone without accompanying interpretation — they need to be told what the results mean.
The Conclusion section presents the outcome of the work by interpreting the findings at a higher level of abstraction than the Discussion and by relating these findings to the motivation stated in the Introduction .

(Papers reporting something other than experiments, such as a new method or technology, typically have different sections in their body, but they include the same Introduction and Conclusion sections as described above.)

Although the above structure reflects the progression of most research projects, effective papers typically break the chronology in at least three ways to present their content in the order in which the audience will most likely want to read it. First and foremost, they summarize the motivation for, and the outcome of, the work in an abstract, located before the Introduction . In a sense, they reveal the beginning and end of the story — briefly — before providing the full story. Second, they move the more detailed, less important parts of the body to the end of the paper in one or more appendices so that these parts do not stand in the readers' way. Finally, they structure the content in the body in theorem-proof fashion, stating first what readers must remember (for example, as the first sentence of a paragraph) and then presenting evidence to support this statement.

The introduction

First, provide some context to orient those readers who are less familiar with your topic and to establish the importance of your work.
Second, state the need for your work, as an opposition between what the scientific community currently has and what it wants.
Third, indicate what you have done in an effort to address the need (this is the task).
Finally, preview the remainder of the paper to mentally prepare readers for its structure, in the object of the document.

Context and need

At the beginning of the Introduction section, the context and need work together as a funnel: They start broad and progressively narrow down to the issue addressed in the paper. To spark interest among your audience — referees and journal readers alike — provide a compelling motivation for the work presented in your paper: The fact that a phenomenon has never been studied before is not, in and of itself, a reason to study that phenomenon.

Write the context in a way that appeals to a broad range of readers and leads into the need. Do not include context for the sake of including context: Rather, provide only what will help readers better understand the need and, especially, its importance. Consider anchoring the context in time, using phrases such as recently , in the past 10 years , or since the early 1990s . You may also want to anchor your context in space (either geographically or within a given research field).

Convey the need for the work as an opposition between actual and desired situations. Start by stating the actual situation (what we have) as a direct continuation of the context. If you feel you must explain recent achievements in much detail — say, in more than one or two paragraphs — consider moving the details to a section titled State of the art (or something similar) after the Introduction , but do provide a brief idea of the actual situation in the Introduction . Next, state the desired situation (what we want). Emphasize the contrast between the actual and desired situations with such words as but , however, or unfortunately .

One elegant way to express the desired part of the need is to combine it with the task in a single sentence. This sentence expresses first the objective, then the action undertaken to reach this objective, thus creating a strong and elegant connection between need and task. Here are three examples of such a combination:

To confirm this assumption , we studied the effects of a range of inhibitors of connexin channels . . . on . . .

To assess whether such multiple-coil sensors perform better than single-signal ones , we tested two of them — the DuoPXK and the GEMM3 — in a field where . . . To form a better view of the global distribution and infectiousness of this pathogen , we examined 1645 postmetamorphic and adult amphibians collected from 27 countries between 1984 and 2006 for the presence of . . .

Task and object

An Introduction is usually clearer and more logical when it separates what the authors have done (the task) from what the paper itself attempts or covers (the object of the document). In other words, the task clarifies your contribution as a scientist, whereas the object of the document prepares readers for the structure of the paper, thus allowing focused or selective reading.

For the task,

use whoever did the work (normally, you and your colleagues) as the subject of the sentence: we or perhaps the authors;
use a verb expressing a research action: measured , calculated , etc.;
set that verb in the past tense.

The three examples below are well-formed tasks.

To confirm this assumption, we studied the effects of a range of inhibitors of connexin channels, such as the connexin mimetic peptides Gap26 and Gap27 and anti-peptide antibodies, on calcium signaling in cardiac cells and HeLa cells expressing connexins.

During controlled experiments, we investigated the influence of the HMP boundary conditions on liver flows.

To tackle this problem, we developed a new software verification technique called oblivious hashing, which calculates the hash values based on the actual execution of the program.

The list below provides examples of verbs that express research actions:

For the object of the document,

use the document itself as the subject of the sentence: this paper , this letter , etc.;
use a verb expressing a communication action: presents , summarizes , etc.;
set the verb in the present tense.

The three examples below are suitable objects of the document for the three tasks shown above, respectively.

This paper clarifies the role of CxHc on calcium oscillations in neonatal cardiac myocytes and calcium transients induced by ATP in HL-cells originated from cardiac atrium and in HeLa cells expressing connexin 43 or 26. This paper presents the flow effects induced by increasing the hepatic-artery pressure and by obstructing the vena cava inferior. This paper discusses the theory behind oblivious hashing and shows how this approach can be applied for local software tamper resistance and remote code authentication.

The list below provides examples of verbs that express communication actions:

Even the most logical structure is of little use if readers do not see and understand it as they progress through a paper. Thus, as you organize the body of your paper into sections and perhaps subsections, remember to prepare your readers for the structure ahead at all levels. You already do so for the overall structure of the body (the sections) in the object of the document at the end of the Introduction . You can similarly prepare your readers for an upcoming division into subsections by introducing a global paragraph between the heading of a section and the heading of its first subsection. This paragraph can contain any information relating to the section as a whole rather than particular subsections, but it should at least announce the subsections, whether explicitly or implicitly. An explicit preview would be phrased much like the object of the document: "This section first . . . , then . . . , and finally . . . "

Although papers can be organized into sections in many ways, those reporting experimental work typically include Materials and Methods , Results , and Discussion in their body. In any case, the paragraphs in these sections should begin with a topic sentence to prepare readers for their contents, allow selective reading, and — ideally — get a message across.

Materials and methods

Results and discussion.

When reporting and discussing your results, do not force your readers to go through everything you went through in chronological order. Instead, state the message of each paragraph upfront: Convey in the first sentence what you want readers to remember from the paragraph as a whole. Focus on what happened, not on the fact that you observed it. Then develop your message in the remainder of the paragraph, including only that information you think you need to convince your audience.

The conclusion

At the end of your Conclusion , consider including perspectives — that is, an idea of what could or should still be done in relation to the issue addressed in the paper. If you include perspectives, clarify whether you are referring to firm plans for yourself and your colleagues ("In the coming months, we will . . . ") or to an invitation to readers ("One remaining question is . . . ").

If your paper includes a well-structured Introduction and an effective abstract, you need not repeat any of the Introduction in the Conclusion . In particular, do not restate what you have done or what the paper does. Instead, focus on what you have found and, especially, on what your findings mean. Do not be afraid to write a short Conclusion section: If you can conclude in just a few sentences given the rich discussion in the body of the paper, then do so. (In other words, resist the temptation to repeat material from the Introduction just to make the Conclusio n longer under the false belief that a longer Conclusion will seem more impressive.)

The abstract

Typically, readers are primarily interested in the information presented in a paper's Introduction and Conclusion sections. Primarily, they want to know the motivation for the work presented and the outcome of this work. Then (and only then) the most specialized among them might want to know the details of the work. Thus, an effective abstract focuses on motivation and outcome; in doing so, it parallels the paper's Introduction and Conclusion .

Accordingly, you can think of an abstract as having two distinct parts — motivation and outcome — even if it is typeset as a single paragraph. For the first part, follow the same structure as the Introduction section of the paper: State the context, the need, the task, and the object of the document. For the second part, mention your findings (the what ) and, especially, your conclusion (the so what — that is, the interpretation of your findings); if appropriate, end with perspectives, as in the Conclusion section of your paper.

Although the structure of the abstract parallels the Introduction and Conclusion sections, it differs from these sections in the audience it addresses. The abstract is read by many different readers, from the most specialized to the least specialized among the target audience. In a sense, it should be the least specialized part of the paper. Any scientist reading it should be able to understand why the work was carried out and why it is important (context and need), what the authors did (task) and what the paper reports about this work (object of the document), what the authors found (findings), what these findings mean (the conclusion), and possibly what the next steps are (perspectives). In contrast, the full paper is typically read by specialists only; its Introduction and Conclusion are more detailed (that is, longer and more specialized) than the abstract.

An effective abstract stands on its own — it can be understood fully even when made available without the full paper. To this end, avoid referring to figures or the bibliography in the abstract. Also, introduce any acronyms the first time you use them in the abstract (if needed), and do so again in the full paper (see Mechanics: Using abbreviations ).

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Writing the Scientific Paper

When you write about scientific topics to specialists in a particular scientific field, we call that scientific writing. (When you write to non-specialists about scientific topics, we call that science writing.)

The scientific paper has developed over the past three centuries into a tool to communicate the results of scientific inquiry. The main audience for scientific papers is extremely specialized. The purpose of these papers is twofold: to present information so that it is easy to retrieve, and to present enough information that the reader can duplicate the scientific study. A standard format with six main part helps readers to find expected information and analysis:

Title--subject and what aspect of the subject was studied.
Abstract--summary of paper: The main reason for the study, the primary results, the main conclusions
Introduction-- why the study was undertaken
Methods and Materials-- how the study was undertaken
Results-- what was found
Discussion-- why these results could be significant (what the reasons might be for the patterns found or not found)

There are many ways to approach the writing of a scientific paper, and no one way is right. Many people, however, find that drafting chunks in this order works best: Results, Discussion, Introduction, Materials & Methods, Abstract, and, finally, Title.

The title should be very limited and specific. Really, it should be a pithy summary of the article's main focus.

"Renal disease susceptibility and hypertension are under independent genetic control in the fawn hooded rat"
"Territory size in Lincoln's Sparrows ( Melospiza lincolnii )"
"Replacement of deciduous first premolars and dental eruption in archaeocete whales"
"The Radio-Frequency Single-Electron Transistor (RF-SET): A Fast and Ultrasensitive Electrometer"

This is a summary of your article. Generally between 50-100 words, it should state the goals, results, and the main conclusions of your study. You should list the parameters of your study (when and where was it conducted, if applicable; your sample size; the specific species, proteins, genes, etc., studied). Think of the process of writing the abstract as taking one or two sentences from each of your sections (an introductory sentence, a sentence stating the specific question addressed, a sentence listing your main techniques or procedures, two or three sentences describing your results, and one sentence describing your main conclusion).

Example One

Hypertension, diabetes and hyperlipidemia are risk factors for life-threatening complications such as end-stage renal disease, coronary artery disease and stroke. Why some patients develop complications is unclear, but only susceptibility genes may be involved. To test this notion, we studied crosses involving the fawn-hooded rat, an animal model of hypertension that develops chronic renal failure. Here, we report the localization of two genes, Rf-1 and Rf-2 , responsible for about half of the genetic variation in key indices of renal impairment. In addition, we localize a gene, Bpfh-1 , responsible for about 26% of the genetic variation in blood pressure. Rf-1 strongly affects the risk of renal impairment, but has no significant effect on blood pressure. Our results show that susceptibility to a complication of hypertension is under at least partially independent genetic control from susceptibility to hypertension itself.

Brown, Donna M, A.P. Provoost, M.J. Daly, E.S. Lander, & H.J. Jacob. 1996. "Renal disease susceptibility and hypertension are under indpendent genetic control in the faun-hooded rat." Nature Genetics , 12(1):44-51.

Example Two

We studied survival of 220 calves of radiocollared moose ( Alces alces ) from parturition to the end of July in southcentral Alaska from 1994 to 1997. Prior studies established that predation by brown bears ( Ursus arctos ) was the primary cause of mortality of moose calves in the region. Our objectives were to characterize vulnerability of moose calves to predation as influenced by age, date, snow depths, and previous reproductive success of the mother. We also tested the hypothesis that survival of twin moose calves was independent and identical to that of single calves. Survival of moose calves from parturition through July was 0.27 ± 0.03 SE, and their daily rate of mortality declined at a near constant rate with age in that period. Mean annual survival was 0.22 ± 0.03 SE. Previous winter's snow depths or survival of the mother's previous calf was not related to neonatal survival. Selection for early parturition was evidenced in the 4 years of study by a 6.3% increase in the hazard of death with each daily increase in parturition date. Although there was no significant difference in survival of twin and single moose calves, most twins that died disappeared together during the first 15 days after birth and independently thereafter, suggesting that predators usually killed both when encountered up to that age.

Key words: Alaska, Alces alces , calf survival, moose, Nelchina, parturition synchrony, predation

Testa, J.W., E.F. Becker, & G.R. Lee. 2000. "Temporal patterns in the survival of twin and single moose ( alces alces ) calves in southcentral Alaska." Journal of Mammalogy , 81(1):162-168.

Example Three

We monitored breeding phenology and population levels of Rana yavapaiensis by use of repeated egg mass censuses and visual encounter surveys at Agua Caliente Canyon near Tucson, Arizona, from 1994 to 1996. Adult counts fluctuated erratically within each year of the study but annual means remained similar. Juvenile counts peaked during the fall recruitment season and fell to near zero by early spring. Rana yavapaiensis deposited eggs in two distinct annual episodes, one in spring (March-May) and a much smaller one in fall (September-October). Larvae from the spring deposition period completed metamorphosis in earlv summer. Over the two years of study, 96.6% of egg masses successfully produced larvae. Egg masses were deposited during periods of predictable, moderate stream flow, but not during seasonal periods when flash flooding or drought were likely to affect eggs or larvae. Breeding phenology of Rana yavapaiensis is particularly well suited for life in desert streams with natural flow regimes which include frequent flash flooding and drought at predictable times. The exotic predators of R. yavapaiensis are less able to cope with fluctuating conditions. Unaltered stream flow regimes that allow natural fluctuations in stream discharge may provide refugia for this declining ranid frog from exotic predators by excluding those exotic species that are unable to cope with brief flash flooding and habitat drying.

Sartorius, Shawn S., and Philip C. Rosen. 2000. "Breeding phenology of the lowland leopard frog ( Rana yavepaiensis )." Southwestern Naturalist , 45(3): 267-273.

Introduction

The introduction is where you sketch out the background of your study, including why you have investigated the question that you have and how it relates to earlier research that has been done in the field. It may help to think of an introduction as a telescoping focus, where you begin with the broader context and gradually narrow to the specific problem addressed by the report. A typical (and very useful) construction of an introduction proceeds as follows:

"Echimyid rodents of the genus Proechimys (spiny rats) often are the most abundant and widespread lowland forest rodents throughout much of their range in the Neotropics (Eisenberg 1989). Recent studies suggested that these rodents play an important role in forest dynamics through their activities as seed predators and dispersers of seeds (Adler and Kestrell 1998; Asquith et al 1997; Forget 1991; Hoch and Adler 1997)." (Lambert and Adler, p. 70)

"Our laboratory has been involved in the analysis of the HLA class II genes and their association with autoimmune disorders such as insulin-dependent diabetes mellitus. As part of this work, the laboratory handles a large number of blood samples. In an effort to minimize the expense and urgency of transportation of frozen or liquid blood samples, we have designed a protocol that will preserve the integrity of lymphocyte DNA and enable the transport and storage of samples at ambient temperatures." (Torrance, MacLeod & Hache, p. 64)

"Despite the ubiquity and abundance of P. semispinosus , only two previous studies have assessed habitat use, with both showing a generalized habitat use. [brief summary of these studies]." (Lambert and Adler, p. 70)

"Although very good results have been obtained using polymerase chain reaction (PCR) amplification of DNA extracted from dried blood spots on filter paper (1,4,5,8,9), this preservation method yields limited amounts of DNA and is susceptible to contamination." (Torrance, MacLeod & Hache, p. 64)

"No attempt has been made to quantitatively describe microhabitat characteristics with which this species may be associated. Thus, specific structural features of secondary forests that may promote abundance of spiny rats remains unknown. Such information is essential to understand the role of spiny rats in Neotropical forests, particularly with regard to forest regeneration via interactions with seeds." (Lambert and Adler, p. 71)

"As an alternative, we have been investigating the use of lyophilization ("freeze-drying") of whole blood as a method to preserve sufficient amounts of genomic DNA to perform PCR and Southern Blot analysis." (Torrance, MacLeod & Hache, p. 64)

"We present an analysis of microhabitat use by P. semispinosus in tropical moist forests in central Panama." (Lambert and Adler, p. 71)

"In this report, we summarize our analysis of genomic DNA extracted from lyophilized whole blood." (Torrance, MacLeod & Hache, p. 64)

Methods and Materials

In this section you describe how you performed your study. You need to provide enough information here for the reader to duplicate your experiment. However, be reasonable about who the reader is. Assume that he or she is someone familiar with the basic practices of your field.

It's helpful to both writer and reader to organize this section chronologically: that is, describe each procedure in the order it was performed. For example, DNA-extraction, purification, amplification, assay, detection. Or, study area, study population, sampling technique, variables studied, analysis method.

Include in this section:

study design: procedures should be listed and described, or the reader should be referred to papers that have already described the used procedure
particular techniques used and why, if relevant
modifications of any techniques; be sure to describe the modification
specialized equipment, including brand-names
temporal, spatial, and historical description of study area and studied population
assumptions underlying the study
statistical methods, including software programs

Example description of activity

Chromosomal DNA was denatured for the first cycle by incubating the slides in 70% deionized formamide; 2x standard saline citrate (SSC) at 70ºC for 2 min, followed by 70% ethanol at -20ºC and then 90% and 100% ethanol at room temperature, followed by air drying. (Rouwendal et al ., p. 79)

Example description of assumptions

We considered seeds left in the petri dish to be unharvested and those scattered singly on the surface of a tile to be scattered and also unharvested. We considered seeds in cheek pouches to be harvested but not cached, those stored in the nestbox to be larderhoarded, and those buried in caching sites within the arena to be scatterhoarded. (Krupa and Geluso, p. 99)

Examples of use of specialized equipment

Oligonucleotide primers were prepared using the Applied Biosystems Model 318A (Foster City, CA) DNA Synthesizer according to the manufacturers' instructions. (Rouwendal et al ., p.78)
We first visually reviewed the complete song sample of an individual using spectrograms produced on a Princeton Applied Research Real Time Spectrum Analyzer (model 4512). (Peters et al ., p. 937)

Example of use of a certain technique

Frogs were monitored using visual encounter transects (Crump and Scott, 1994). (Sartorius and Rosen, p. 269)

Example description of statistical analysis

We used Wilcox rank-sum tests for all comparisons of pre-experimental scores and for all comparisons of hue, saturation, and brightness scores between various groups of birds ... All P -values are two-tailed unless otherwise noted. (Brawner et al ., p. 955)

This section presents the facts--what was found in the course of this investigation. Detailed data--measurements, counts, percentages, patterns--usually appear in tables, figures, and graphs, and the text of the section draws attention to the key data and relationships among data. Three rules of thumb will help you with this section:

present results clearly and logically
avoid excess verbiage
consider providing a one-sentence summary at the beginning of each paragraph if you think it will help your reader understand your data

Remember to use table and figures effectively. But don't expect these to stand alone.

Some examples of well-organized and easy-to-follow results:

Size of the aquatic habitat at Agua Caliente Canyon varied dramatically throughout the year. The site contained three rockbound tinajas (bedrock pools) that did not dry during this study. During periods of high stream discharge seven more seasonal pools and intermittent stretches of riffle became available. Perennial and seasonal pool levels remained stable from late February through early May. Between mid-May and mid-July seasonal pools dried until they disappeared. Perennial pools shrank in surface area from a range of 30-60 m² to 3-5- M². (Sartorius and Rosen, Sept. 2000: 269)

Notice how the second sample points out what is important in the accompanying figure. It makes us aware of relationships that we may not have noticed quickly otherwise and that will be important to the discussion.

A similar test result is obtained with a primer derived from the human ß-satellite... This primer (AGTGCAGAGATATGTCACAATG-CCCC: Oligo 435) labels 6 sites in the PRINS reaction: the chromosomes 1, one pair of acrocentrics and, more weakly, the chromosomes 9 (Fig. 2a). After 10 cycles of PCR-IS, the number of sites labeled has doubled (Fig. 2b); after 20 cycles, the number of sites labeled is the same but the signals are stronger (Fig. 2c) (Rouwendal et al ., July 93:80).

Related Information: Use Tables and Figures Effectively

Do not repeat all of the information in the text that appears in a table, but do summarize it. For example, if you present a table of temperature measurements taken at various times, describe the general pattern of temperature change and refer to the table.

"The temperature of the solution increased rapidly at first, going from 50º to 80º in the first three minutes (Table 1)."

You don't want to list every single measurement in the text ("After one minute, the temperature had risen to 55º. After two minutes, it had risen to 58º," etc.). There is no hard and fast rule about when to report all measurements in the text and when to put the measurements in a table and refer to them, but use your common sense. Remember that readers have all that data in the accompanying tables and figures, so your task in this section is to highlight key data, changes, or relationships.

In this section you discuss your results. What aspect you choose to focus on depends on your results and on the main questions addressed by them. For example, if you were testing a new technique, you will want to discuss how useful this technique is: how well did it work, what are the benefits and drawbacks, etc. If you are presenting data that appear to refute or support earlier research, you will want to analyze both your own data and the earlier data--what conditions are different? how much difference is due to a change in the study design, and how much to a new property in the study subject? You may discuss the implication of your research--particularly if it has a direct bearing on a practical issue, such as conservation or public health.

This section centers on speculation . However, this does not free you to present wild and haphazard guesses. Focus your discussion around a particular question or hypothesis. Use subheadings to organize your thoughts, if necessary.

This section depends on a logical organization so readers can see the connection between your study question and your results. One typical approach is to make a list of all the ideas that you will discuss and to work out the logical relationships between them--what idea is most important? or, what point is most clearly made by your data? what ideas are subordinate to the main idea? what are the connections between ideas?

Achieving the Scientific Voice

Eight tips will help you match your style for most scientific publications.

Develop a precise vocabulary: read the literature to become fluent, or at least familiar with, the sort of language that is standard to describe what you're trying to describe.
Once you've labeled an activity, a condition, or a period of time, use that label consistently throughout the paper. Consistency is more important than creativity.
Define your terms and your assumptions.
Include all the information the reader needs to interpret your data.
Remember, the key to all scientific discourse is that it be reproducible . Have you presented enough information clearly enough that the reader could reproduce your experiment, your research, or your investigation?
When describing an activity, break it down into elements that can be described and labeled, and then present them in the order they occurred.
When you use numbers, use them effectively. Don't present them so that they cause more work for the reader.
Include details before conclusions, but only include those details you have been able to observe by the methods you have described. Do not include your feelings, attitudes, impressions, or opinions.
Research your format and citations: do these match what have been used in current relevant journals?
Run a spellcheck and proofread carefully. Read your paper out loud, and/ or have a friend look over it for misspelled words, missing words, etc.

Applying the Principles, Example 1

The following example needs more precise information. Look at the original and revised paragraphs to see how revising with these guidelines in mind can make the text clearer and more informative:

Before: Each male sang a definite number of songs while singing. They start with a whistle and then go from there. Each new song is always different, but made up an overall repertoire that was completed before starting over again. In 16 cases (84%), no new songs were sung after the first 20, even though we counted about 44 songs for each bird.

After: Each male used a discrete number of song types in his singing. Each song began with an introductory whistle, followed by a distinctive, complex series of fluty warbles (Fig. 1). Successive songs were always different, and five of the 19 males presented their entire song repertoire before repeating any of their song types (i.e., the first IO recorded songs revealed the entire repertoire of 10 song types). Each song type recurred in long sequences of singing, so that we could be confident that we had recorded the entire repertoire of commonly used songs by each male. For 16 of the 19 males, no new song types were encountered after the first 20 songs, even though we analyzed and average of 44 songs/male (range 30-59).

Applying the Principles, Example 2

In this set of examples, even a few changes in wording result in a more precise second version. Look at the original and revised paragraphs to see how revising with these guidelines in mind can make the text clearer and more informative:

Before: The study area was on Mt. Cain and Maquilla Peak in British Columbia, Canada. The study area is about 12,000 ha of coastal montane forest. The area is both managed and unmanaged and ranges from 600-1650m. The most common trees present are mountain hemlock ( Tsuga mertensiana ), western hemlock ( Tsuga heterophylla ), yellow cedar ( Chamaecyparis nootkatensis ), and amabilis fir ( Abies amabilis ).

After: The study took place on Mt. Cain and Maquilla Peak (50'1 3'N, 126'1 8'W), Vancouver Island, British Columbia. The study area encompassed 11,800 ha of coastal montane forest. The landscape consisted of managed and unmanaged stands of coastal montane forest, 600-1650 m in elevation. The dominant tree species included mountain hemlock ( Tsuga mertensiana ), western hemlock ( Tsuga heterophylla ), yellow cedar ( Chamaecyparis nootkatensis ), and amabilis fir ( Abies amabilis ).

Two Tips for Sentence Clarity

Although you will want to consider more detailed stylistic revisions as you become more comfortable with scientific writing, two tips can get you started:

First, the verb should follow the subject as soon as possible.

Really Hard to Read : "The smallest of the URF's (URFA6L), a 207-nucleotide (nt) reading frame overlapping out of phase the NH2- terminal portion of the adenosinetriphosphatase (ATPase) subunit 6 gene has been identified as the animal equivalent of the recently discovered yeast H+-ATPase subunit gene."

Less Hard to Read : "The smallest of the UR-F's is URFA6L, a 207-nucleotide (nt) reading frame overlapping out of phase the NH2-terminal portion of the adenosinetriphosphatase (ATPase) subunit 6 gene; it has been identified as the animal equivalent of the recently discovered yeast H+-ATPase subunit 8 gene."

Second, place familiar information first in a clause, a sentence, or a paragraph, and put the new and unfamiliar information later.

More confusing : The epidermis, the dermis, and the subcutaneous layer are the three layers of the skin. A layer of dead skin cells makes up the epidermis, which forms the body's shield against the world. Blood vessels, carrying nourishment, and nerve endings, which relay information about the outside world, are found in the dermis. Sweat glands and fat cells make up the third layer, the subcutaneous layer.

Less confusing : The skin consists of three layers: the epidermis, the dermis, and the subcutaneous layer. The epidermis is made up of dead skin cells, and forms a protective shield between the body and the world. The dermis contains the blood vessels and nerve endings that nourish the skin and make it receptive to outside stimuli. The subcutaneous layer contains the sweat glands and fat cells which perform other functions of the skin.

Bibliography

Scientific Writing for Graduate Students . F. P. Woodford. Bethesda, MD: Council of Biology Editors, 1968. [A manual on the teaching of writing to graduate students--very clear and direct.]
Scientific Style and Format . Council of Biology Editors. Cambridge: Cambridge University Press, 1994.
"The science of scientific writing." George Gopen and Judith Swann. The American Scientist , Vol. 78, Nov.-Dec. 1990. Pp 550-558.
"What's right about scientific writing." Alan Gross and Joseph Harmon. The Scientist , Dec. 6 1999. Pp. 20-21.
"A Quick Fix for Figure Legends and Table Headings." Donald Kroodsma. The Auk , 117 (4): 1081-1083, 2000.

Wortman-Wunder, Emily, & Kate Kiefer. (1998). Writing the Scientific Paper. Writing@CSU . Colorado State University. https://writing.colostate.edu/resources/writing/guides/.

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The science essay, course description.

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How to Write a Scientific Essay

When writing any essay it’s important to always keep the end goal in mind. You want to produce a document that is detailed, factual, about the subject matter and most importantly to the point.

Writing scientific essays will always be slightly different to when you write an essay for say English Literature . You need to be more analytical and precise when answering your questions. To help achieve this, you need to keep three golden rules in mind.

Analysing the question, so that you know exactly what you have to do

Planning your answer

Writing the essay

Now, let’s look at these steps in more detail to help you fully understand how to apply the three golden rules.

Analysing the question

Start by looking at the instruction. Essays need to be written out in continuous prose. You shouldn’t be using bullet points or writing in note form.
If it helps to make a particular point, however, you can use a diagram providing it is relevant and adequately explained.
Look at the topic you are required to write about. The wording of the essay title tells you what you should confine your answer to – there is no place for interesting facts about other areas.

The next step is to plan your answer. What we are going to try to do is show you how to produce an effective plan in a very short time. You need a framework to show your knowledge otherwise it is too easy to concentrate on only a few aspects.

For example, when writing an essay on biology we can divide the topic up in a number of different ways. So, if you have to answer a question like ‘Outline the main properties of life and system reproduction’

The steps for planning are simple. Firstly, define the main terms within the question that need to be addressed. Then list the properties asked for and lastly, roughly assess how many words of your word count you are going to allocate to each term.

Writing the Essay

The final step (you’re almost there), now you have your plan in place for the essay, it’s time to get it all down in black and white. Follow your plan for answering the question, making sure you stick to the word count, check your spelling and grammar and give credit where credit’s (always reference your sources).

How Tutors Breakdown Essays

An exceptional essay

reflects the detail that could be expected from a comprehensive knowledge and understanding of relevant parts of the specification
is free from fundamental errors
maintains appropriate depth and accuracy throughout
includes two or more paragraphs of material that indicates greater depth or breadth of study

A good essay

An average essay

contains a significant amount of material that reflects the detail that could be expected from a knowledge and understanding of relevant parts of the specification.

In practice this will amount to about half the essay.

is likely to reflect limited knowledge of some areas and to be patchy in quality
demonstrates a good understanding of basic principles with some errors and evidence of misunderstanding

A poor essay

contains much material which is below the level expected of a candidate who has completed the course
Contains fundamental errors reflecting a poor grasp of basic principles and concepts

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How to Write a Scientific Essay to Meet Academic Standards

Students compose a great variety of academic assignments. Some of them are pretty complicated. Nonetheless, they are pretty interesting and develop our skills and improve knowledge. One of the stumbling stones in essay writing is the academic discipline. They all are different, and each has its own difficulties. Thus, many students wish to learn how to write a scientific essay.

This discipline requires great dedication. You ought to be really scientific, make in-depth research on every detail because even the slightest thing may change the course of events. It’s important to be familiar with other works related to your study, find the latest news and similar things. The scientific essay meaning is crucial as it explains complex events, things or terms from the scientific viewpoint. It’s not a simple essay about how you feel today. That is a very important, durable and complex labor.

Therefore, this assignment cannot be referred to as the easiest research projects. Nonetheless, it is undoubtedly one of the most exciting and challenging. Try to accomplish it with our assistance.

Related essays:

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Writing a Scientific Essay: Smart Tips

There are specific recommendations you should know about this paper. There is nothing really new about the process of writing a scientific essay. The things you should fulfill are similar to other research papers. Nevertheless, they are helpful, and you should not skip a single stage.

Firstly, you should choose your topic. It is expected to be interesting. Try to pick a universal theme. It should be interesting for you and your readers. In the meanwhile, it ought to discover some issue and propose some solutions.

Once you identify your topic, search for the appropriate information. Undoubtedly, you should take some notes. It’s not possible to memorize all facts and statistics. Therefore, note all the things related to your project. Afterward, throw out insignificant data and keep the most effective evidence.

Depending on the topic and found data, craft an outline. It should include all stages of your writing – the introduction, thesis, main body, conclusion, and references.

A good beginning makes the half of your success. Therefore, pay particular attention to this matter. It should be intriguing. Use the strong first line to captivate your audience. After you grab attention, introduce a thesis statement. It should clearly explain your primary purpose.

The main body continues your story from the thesis. Use relevant facts, figures, statistics, etc., to support your claim. You cannot simply say that this or that phenomenon is possible. That is scientific research. It demands the approved facts and proofs.

Your conclusion is the summarization of the entire paper. Mention your central question once again and remind of its importance. Afterward, mention the results of your study and their value.

Scientific Essay Format: Essential Points to Know

It goes beyond all doubts that the format of an assignment is crucial as well. You should know all the details concerning your scientific essay format. There are such writing formats as MLA, APA, Chicago, Harvard, Vancouver, etc. Learn everything about the proper citing and preparation of the reference list. Every part of your writing ought to be fulfilled correctly. Your paper should contain:

Materials and Methods
Acknowledgments

Your title tells the reader your name, the title of the research, the course number, and similar points. The abstract reveals your purpose, contains the introduction, main plot, and the conclusion.

It’s required to mention the information and methods you used to prove your opinion. Shed more light on the outcomes of your research. Afterward, you should discuss them. Explain their meaning to the readers and why they are so important.

References contain the data you used in your paper. Prepare them following the assigned format. Your acknowledgments contain information about all people who somehow contributed to the development of your project.

Scientific Essay Topics: Engaging and Interesting Variants

Under the condition, you cannot create scientific essay topics on your own use our help. At times, people need only a few examples to understand how to complete different tasks. Make allowances for the following suggestions:

What are a scientific revolution and its consequences for the humanity?
Can molecular biology find the keys to correct gene failure?
What are the measures to linger the process of aging?
Reveal the importance of scientific attitude for the current society.
Is it true that life existed on Mars? What are the main theories?
What methodologies can prevent the occurrence of schizophrenia?
Is stem cell therapy effective against autism?
The consequences of scientific revolution and enlightenment in the second part of the 20th century.
Is Biocomputing the future of the humankind?
Which alternatives are able to save polluted areas and their flora and fauna?

Memorize these suggestions. They highlight important issues, which are relevant for all times. Craft your own concepts using our list.

Scientific Essay | How To Write It, Parts And Characteristics

We explain what a scientific essay is, its characteristics and the parts that make it up. Also, how to write a scientific essay?

What is a scientific essay?

A scientific essay is a type of prose writing in which the author gives his opinion or position on a particular topic based on certain objective information that comes from laws or scientifically reliable evidence.

The scientific essay uses formal language , although not necessarily elaborate or sophisticated, to convey an idea or present a thought of the author. It is made up of two fundamental parts: an objective part, in which the thesis or scientific theory is exposed, and another subjective part in which the writer of the essay presents conclusions or hypotheses on the issue raised.

The type of content that a scientific essay addresses is varied, but always revolves around science-related topics . In addition, the essays vary among themselves in length, objective and audience to which they are directed.

Characteristics of a scientific essay

Some of the main characteristics of a scientific essay are:

It must be original and unpublished . An essay must present an opinion or point of view drawn up by the author himself, so subjective information from other authors cannot be copied or replicated.
You can use a free theme . There is no specific area or topic for the development of a scientific essay, but the author can choose the subject that is of interest to him.
It should only address one topic . A scientific essay does not address multiple topics at once, but rather focuses on expressing a single, central idea. Then you can address related or secondary topics, but always in relation to the main topic.
Use a scientific theory or law as a basis . The starting point of any scientific essay is to investigate a topic and then develop the conclusions or hypotheses.
It must be synthetic . All scientific essays must be brief but must always include relevant data. In general terms, although it depends on the topic addressed, scientific essays do not usually exceed four or five A4 pages.
It has stages . A scientific essay is carried out by following certain steps that guide the author and allow him to do a good job.
It is written in simple and formal language . For the writing of a scientific essay, a formal and objective language must be used, although it does not have to be strictly scientific.
It must have order and coherence . For the organization of an essay, it is advisable to follow certain guidelines or order when organizing and capturing the information.
Bibliography must be included . Any scientific essay must include the sources from which the scientific data is obtained. This is extremely important to give seriousness and confidence in the essay and to give credit to the authors of the scientific theories or laws.

How to do a scientific essay?

There are certain steps or stages that can be carried out when doing a scientific essay. These are:

Selection of the research area . The author of the essay chooses the field or discipline on which he wants to investigate.
Research . We proceed to the reading of different topics of interest that allow reducing the field of action and result in the topic on which it will be investigated.
Delimitation of the subject . After defining the theme, the author recognizes something that he does not understand or is interesting about a theory and discovers the axis of his essay.
Information search . The author investigates everything that is published on that particular topic and collects the data and information he needs to later refute or affirm his own hypotheses or conclusions.
Organization and selection of information . The author uses all the information previously collected and chooses which is the essential information, which will be discarded and which will be complementary data.
Elaboration of an outline . From the information collected, the most important concepts are extracted and the primary and secondary ideas are recognized. The data of interest and the conclusions drawn from the research are turned over on a sheet.
Preparation of a draft . The order that the information will have within the essay is defined and the writing begins.
Writing the essay . The final version of the essay is written and contents of the draft can be added or deleted. In this instance, attention must be paid to the correction and editing of the writing, since it is important that the essay does not have errors in style or in spelling and grammar.

Parts of a scientific essay

A scientific essay consists of the following elements:

Title . It is the name that the scientific essay will bear. It is important that it is original and refers to the content of the writing.
Introduction . The topic that the essay will address is raised and the hypotheses or what explains the reason for the choice of that topic are formulated.
Development . The ideas or data that support the author's position are presented and developed and the bases on which the author starts for the investigation are raised and made known . Information and data from certified sources are used in the development of the essay and opinions and points of view of the author may be included (although always duly justified). The essay must be a personal and original analysis and, in the event that extracts or content from other authors are cited, the source must be specified.
Conclusions . The conclusions reached by the author after the investigation and analysis of information are detailed.
Bibliography. The sources of information used throughout the research and writing process are listed.

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Scientific Essay Format: Definition and Features

A scientific essay requires students to analyze a scientific problem. Based on the information they get, they have to develop a workable solution. The writer is expected to provide their opinion on the issue. The essay features an abstract, introduction, methodology, results, discussion, and references. The introduction provides the hypotheses to be tested. The methodology describes in detail how the problem was tested. All information provided should be scientifically verifiable. The writer must ensure they write a high-quality essay to get good grades.

What is a scientific essay?

A scientific essay is an article or journal that addresses a specific problem. It follows the standards of academic essay writing. The essay must include the main structure - introduction, body, and conclusion. The student captures more details, such as an abstract, methodology, and results. The essay exposes students to effective scientific writing. It helps build their academic profile and increase their credibility. It exposes them to scientific research and insights. Mainly, a scientific essay format follows the APA citation style.

Students are expected to write several essays every semester. Lecturers expect the writer to submit a paper that stands out. It is not easy to write a strong paper that is credible and informative. You can submit a paper that stands out by getting essay writing help online. You only need to chat with essay helper on EduBirdie and give him your essay details. The writer will follow your instructions and create a highly detailed essay. Every time you need essay help, you get to choose your writer based on your need.

Features of a scientific essay

A scientific essay is divided into several sections. Each discusses specific issues based on the defined science essay format. It features an introduction, abstract, methodology, results, discussions, and references.

Abstract/Summary

An abstract provides a summary of the problem. It highlights the key points to be investigated and discussed. It discusses the activities that were done but not in detail. It is necessary to understand well how to write a scientific essay. Usually, the abstract is written last.

Introduction

The introduction is brief information about the background of the problem. It helps the reader understand why the study was conducted. It gives an overview of the research that was previously done. It discusses the gaps that the current research will cover. The writer must state the goals plus the questions the research will answer. The hypotheses should be stated based on the type of essay at hand.

Methodology

It is necessary to understand what kind of writing is found in a scientific essay. The essay could be descriptive, narrative, or compare and contrast. The methodology explains several features.

Type of research conducted
The purpose of each procedure
How data was collected and analyzed
Reasons for using the tools

In the essay format definition, results discuss the outcomes. It presents what was found after the tests or study was done. The writer must discuss the results based on what was expected. It discusses their connection with previous studies.

Discussions

This section discusses the meaning of the results obtained. It provides details of their importance and relevance. It explains what was found and an evaluation of the supporting information.

If a writer learns how to start a science essay, references should not be a problem. The writer needs to be keen on the citation format required. References give the writer credibility. It proves they spent time in research and they didn’t copy another author’s work .

What makes a scientific essay good?

It is necessary to learn how to write a science essay before starting the writing process. These features make a scientific essay stand out.

Make it precise: Accuracy is crucial in scientific essay writing. The writer must capture detailed information. A scientific paper must be objective, thorough, and use the exact language.

Provide clarity: The reader should not struggle to understand what the writer meant . All information provided should be clear. The complex terms used should be explained in the index. To make information clear, use tables, charts, figures, and images.

Know the audience: Scientific papers are mostly written for a scientific audience. It’s scientists who will mostly be interested in research information. Other audiences might also be interested in reading the details.

Well organized: The essay should include all the components of an academic paper. It must contain clear sentences and paragraphs. The information should flow flawlessly from one point to the next.

A scientific essay requires students to research a certain problem. They must provide solutions and include their views or recommendations. The essay comprises an abstract, introduction, method, results, discussion, and references. The writer needs to use charts, tables, and figures to make the information clear. He must directly write to his audience and keep the essay well organized.

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Scientific Progress

Science is often distinguished from other domains of human culture by its progressive nature: in contrast to art, religion, philosophy, morality, and politics, there exist clear standards or normative criteria for identifying improvements and advances in science. For example, the historian of science George Sarton argued that “the acquisition and systematization of positive knowledge are the only human activities which are truly cumulative and progressive,” and “progress has no definite and unquestionable meaning in other fields than the field of science” (Sarton 1936). However, the traditional cumulative view of scientific knowledge was effectively challenged by many philosophers of science in the 1960s and the 1970s, and thereby the notion of progress was also questioned in the field of science. Debates on the normative concept of progress are at the same time concerned with axiological questions about the aims and goals of science. The task of philosophical analysis is to consider alternative answers to the question: What is meant by progress in science? This conceptual question can then be complemented by the methodological question: How can we recognize progressive developments in science? Relative to a definition of progress and an account of its best indicators, one may then study the factual question: To what extent, and in which respects, is science progressive?

1. The Study of Scientific Change

2.1 aspects of scientific progress, 2.2 progress vs. development, 2.3 progress, quality, impact, 2.4 progress and goals, 2.5 progress and rationality, 3.1 realism and instrumentalism, 3.2 empirical success and problem-solving, 3.3 explanatory power, unification, and simplicity, 3.4 truth and information, 3.5 truthlikeness, 3.6 knowledge and understanding, 4. is science progressive, other internet resources, related entries.

The idea that science is a collective enterprise of researchers in successive generations is characteristic of the Modern Age (Nisbet 1980). Classical empiricists (Francis Bacon) and rationalists (René Descartes) of the seventeenth century urged that the use of proper methods of inquiry guarantees the discovery and justification of new truths. This cumulative view of scientific progress was an important ingredient in the optimism of the eighteenth century Enlightenment, and it was incorporated in the 1830s in Auguste Comte’s program of positivism: by accumulating empirically certified truths science also promotes progress in society. Other influential trends in the nineteenth century were the Romantic vision of organic growth in culture, Hegel’s dynamic account of historical change, and the theory of evolution. They all inspired epistemological views (e.g., among Marxists and pragmatists) which regarded human knowledge as a process. Philosopher-scientists with an interest in the history of science (William Whewell, Charles Peirce, Ernst Mach, Pierre Duhem) gave interesting analyses of some aspects of scientific change.

In the early twentieth century, analytic philosophers of science started to apply modern logic to the study of science. Their main focus was the structure of scientific theories and patterns of inference (Suppe 1977). This “synchronic” investigation of the “finished products” of scientific activities was questioned by philosophers who wished to pay serious attention to the “diachronic” study of scientific change. Among these contributions one can mention N.R. Hanson’s Patterns of Discovery (1958), Karl Popper’s The Logic of Scientific Discovery (1959) and Conjectures and Refutations (1963), Thomas Kuhn’s The Structure of Scientific Revolutions (1962), Paul Feyerabend’s incommensurability thesis (Feyerabend 1962), Imre Lakatos’ methodology of scientific research programmes (Lakatos and Musgrave 1970), and Larry Laudan’s Progress and Its Problems (1977). Darwinist models of evolutionary epistemology were advocated by Popper’s Objective Knowledge: An Evolutionary Approach (1972) and Stephen Toulmin’s Human Understanding (1972). These works challenged the received view about the development of scientific knowledge and rationality. Popper’s falsificationism, Kuhn’s account of scientific revolutions, and Feyerabend’s thesis of meaning variance shared the view that science does not grow simply by accumulating new established truths upon old ones. Except perhaps during periods of Kuhnian normal science, theory change is not cumulative or continuous: the earlier results of science will be rejected, replaced, and reinterpreted by new theories and conceptual frameworks. Popper and Kuhn differed, however, in their definitions of progress: the former appealed to the idea that successive theories may approach towards the truth, while the latter characterized progress in terms of the problem-solving capacity of theories.

Since the mid-1970s, a great number of philosophical works have been published on the topics of change, development, and progress in science (Harré 1975; Stegmüller 1976; Howson 1976; Rescher 1978; Radnitzky and Andersson 1978, 1979; Niiniluoto and Tuomela 1979; Dilworth 1981; Smith 1981; Hacking 1981; Schäfer 1983; Niiniluoto 1984; Laudan 1984a; Rescher 1984; Pitt 1985; Radnitzky and Bartley 1987; Callebaut and Pinxten 1987; Balzer et al . 1987; Hull 1988; Gavroglu et al . 1989; Kitcher 1993; Pera 1994; Chang 2004; Maxwell 2017; Shan 2023; Rowbottom 2023). These studies have also led to many important novelties being added to the toolbox of philosophers of science. One of them is the systematic study of inter-theory relations, such as reduction (Balzer et al . 1984; Pearce 1987; Balzer 2000; Jonkisz 2000; Hoyningen-Huene and Sankey 2001), correspondence (Krajewski 1977; Nowak 1980; Pearce and Rantala 1984; Nowakowa and Nowak 2000; Rantala 2002), and belief revision (Gärdenfors, 1988; Aliseda, 2006). A new tool that is employed in many defenses of realist views of scientific progress (Niiniluoto 1980, 2014; Aronson, Harré, and Way 1994; Kuipers 2000, 2019; Garcia-Lapena 2023) is the notion of truthlikeness or verisimilitude (Popper 1963, 1970).

Besides individual statements and theories, there is also a need to consider temporally developing units of scientific activity and achievement: Kuhn’s paradigm-directed normal science, Lakatos’ research programme, Laudan’s research tradition, Wolfgang Stegmüller’s (1976) dynamic theory evolution, Philip Kitcher’s (1993) consensus practice, and Hasok Chang’s (2012) systems of practice. Kuhn refined his concept of paradigm to “a disciplinary matrix,” which is a constellation of symbolic generalizations, models, values, and exemplary problem solutions. Rachel Ankeny and Sabina Leonelli (2016) define an alternative to Kuhnian paradigms in their concept of “repertoire,” understood as a well-aligned assemblage of the skills, behaviors, and material, social, and epistemic components used by a collaborative group of researchers. Nancy Cartwright et al . (2022) argue that, instead of rigorous and objective methods, reliability is guaranteed by the “tangle” of science, i.e., the working together of theories, methods, experiments, instruments, classification schemes, habits of data collection, forms of analysis, and measuring techniques.

Lively interest about the development of science promoted close co-operation between historians and philosophers of science. For example, case studies of historical examples (e.g., the replacement of Newton’s classical mechanics by quantum theory and theory of relativity) have inspired many philosophical treatments of scientific revolutions. Historical case studies were important for philosophers who started to study scientific discovery (Hanson 1958; Nickles 1980). Historically oriented philosophers have shown how instruments and measurements have promoted the progress of physics and chemistry (Rheinberger 1997; Chang 2004). Experimental psychologists have argued that the strive for broad and simple explanations shapes learning and inference (Lombrozo 2016). Further interesting material for philosophical discussions about scientific progress is provided by quantitative approaches in the study of the growth of scientific publications (de Solla Price 1963; Rescher 1978) and science indicators (Elkana et al . 1978). Sociologists of science have studied the dynamic interaction between the scientific community and other social institutions. With their influence, philosophers have analyzed the role of social and cultural values in the development of science (Longino 2002, Pestre 2003). One of the favorite topics of sociologists has been the emergence of new scientific specialties (Mulkay 1975; Niiniluoto 1995b). Sociologists are also concerned with the pragmatic problem of progress: what is the best way of organizing research activities in order to promote scientific advance. In this way, models of scientific change turn out to be relevant to issues of science policy (Böhme 1977; Schäfer 1983).

2. The Concept of Progress

Science is a multi-layered complex system involving a community of scientists engaged in research using scientific methods in order to produce new knowledge. Thus, the notion of science may refer to a social institution, the researchers, the research process, the method of inquiry, and scientific knowledge. The concept of progress can be defined relative to each of these aspects of science. Hence, different types of progress can be distinguished relative to science: economical (the increased funding of scientific research), professional (the rising status of the scientists and their academic institutions in the society), educational (the increased skill and expertise of the scientists), methodical (the invention of new methods of research, the refinement of scientific instruments), and cognitive (increase or advancement of scientific knowledge). These types of progress have to be conceptually distinguished from advances in other human activities, even though it may turn out that scientific progress has at least some factual connections with technological progress (increased effectiveness of tools and techniques) and social progress (economic prosperity, quality of life, justice in society).

All of these aspects of scientific progress may involve different considerations, so that there is no single concept that would cover all of them. For our purposes, it is appropriate here to concentrate only on cognitive progress, i.e., to give an account of advances of science in terms of its success in knowledge-seeking or truth-seeking. Such progress in modern science presupposes that scientific information is made available in published and peer reviewed articles and monographs, while economical, professional, educational, and methodical advances promote scientific progress but do not constitute cognitive progress (cf. Dellsén 2023). Similarly, technological progress and social progress may be consequences of scientific progress without constituting cognitive progress.

“Progress” is an axiological or a normative concept, which should be distinguished from such neutral descriptive terms as “change” and “development” (Niiniluoto 1995a). In general, to say that a step from stage $A$ to stage $B$ constitutes progress means that $B$ is an improvement over $A$ in some respect, i.e., $B$ is better than $A$ relative to some standards or criteria. In science, it is a normative demand that all contributions to research should yield some cognitive profit, and their success in this respect can be assessed before publication by referees (peer review) and after publication by colleagues. Hence, the theory of scientific progress is not merely a descriptive account of the patterns of developments that science has in fact followed. Rather, it should give a specification of the values or aims that can be used as the constitutive criteria for “good science.”

The “naturalist” program in science studies suggests that normative questions in the philosophy of science can be reduced to historical and sociological investigations of the actual practice of science. In this spirit, Laudan has defended the project of testing philosophical models of scientific change by the history of science: such models, which are “often couched in normative language,” can be recast “into declarative statements about how science does behave” (Laudan et al . 1986; Donovan et al . 1988). It may be the case that most scientific work, at least the best science of each age, is also good science. But it is also evident that scientists often have different opinions about the criteria of good science, and rival researchers and schools make different choices in their preference of theories and research programs. Therefore, it can be argued against the naturalists that progress should not be defined by the actual developments of science: the definition of progress should give us a normative standard for appraising the choices that the scientific communities have made, could have made, are just now making, and will make in the future. The task of finding and defending such standards is a genuinely philosophical one which can be enlightened by history and sociology but which cannot be reduced to empirical studies of science. For the same reason, Mizrahi’s (2013) empirical observation that scientists talk about the aim of science in terms of knowledge rather than merely truth cannot settle the philosophical debate about scientific progress (cf. Bird 2007; Niiniluoto 2014).

For many goal-directed activities it is important to distinguish between quality and progress . Quality is primarily an activity-oriented concept, concerning the skill and competence in the performance of some task. Progress is a result-oriented concept, concerning the success of a product relative to some goal. All acceptable work in science has to fulfill certain standards of quality. But it seems that there are no necessary connections between quality and progress in science. Sometimes very well-qualified research projects fail to produce important new results, while less competent but more lucky works lead to success. Nevertheless, the skillful use of the methods of science will make progress highly probable. Hence, the best practical strategy in promoting scientific progress is to support high-quality research.

Following the pioneering work of Derek de Solla Price (1963) in “scientometrics,” quantitative science indicators have been proposed as measures of scientific activity (Elkana et al . 1978). For example, output measures like publication counts are measures of scholarly achievement, but it is problematic whether such a crude measure is sufficient to indicate quality (cf. Chotkowski La Follette 1982). Another example of a science indicator, citation index , is an indicator for the “impact” of a publication and for the “visibility” of its author within the scientific community. The relative importance and quality of a journal is often measured by its impact factor , defined by the yearly mean number of citations of its published articles in the last two years. Thus, the number of articles in refereed journals with a high impact factor is an indicator of the quality of their author, but it is clear that this indicator cannot yet define what progress means, since publications may contribute different amounts to the advance of scientific knowledge. “Rousseau’s Law” proposed by Nicholas Rescher (1978) marks off a certain part (the square root) of the total number of publications as “important”, but this is merely an alleged statistical regularity.

Martin and Irvine (1983) suggest that the concept of scientific progress should be linked to the notion of impact , i.e., the actual influence of research to the surrounding scientific activities at a given time. It is no doubt correct that one cannot advance scientific knowledge without influencing the epistemic state of the scientific community. But the impact of a publication as such only shows that it has successfully “moved” the scientific community in some direction. If science is goal-directed, then we must acknowledge that movement in the wrong direction does not constitute progress.

The failure of science indicators to function as definitions of scientific progress is due to the fact that they do not take into account the semantic content of scientific publications. To determine whether a work $W$ gives a contribution to scientific progress, we have to specify what $W$ says (alternatively: what problems $W$ solves) and then relate this content of $W$ to the knowledge situation of the scientific community at the time of the publication of $W$. For the same reason, research assessment exercises may use science indicators as tools, but ultimately they have to rely on the judgment of peers who have substantial knowledge in the field.

Progress is a goal-relative concept. But even when we consider science as a knowledge-seeking cognitive enterprise, there is no reason to assume that the goal of science is one-dimensional. In contrast, as Isaac Levi’s classic Gambling With Truth (1967) argued, the cognitive aim of scientific inquiry has to be defined as a weighted combination of several different, and even conflicting, epistemic utilities . As we shall see in Section 3, alternative theories of scientific progress can be understood as specifications of such epistemic utilities. For example, they might include truth and information (Levi 1967; see also Popper 1959, 1963) or explanatory and predictive power (Hempel 1965). Kuhn’s (1977) list of the values of science includes accuracy, consistency, scope, simplicity, and fruitfulness.

A goal may be accessible in the sense that it can be reached in a finite number of steps in a finite time. A goal is utopian if it cannot be reached or even approached. Thus, utopian goals cannot be rationally pursued, since no progress can be made in an attempt to reach them. Walking to the moon is a utopian task in this sense. However, not all inaccessible goals are utopian: an unreachable goal, such as being morally perfect, can function as a regulative principle in Kant’s sense, if it guides our behavior so that we are able to make progress towards it.

The classical sceptic argument against science, repeated by Laudan (1984a), is that knowing the truth is a utopian task. Kant’s answer to this argument was to regard truth as a regulative principle for science. Charles S. Peirce, the founder of American pragmatism, argued that the access to the truth as the ideal limit of scientific inquiry is “destined” or guaranteed in an “indefinite” community of investigators. Almeder’s (1983) interpretation of Peirce’s view of scientific progress is that there is only a finite number of scientific problems and they will all be solved in a finite time. However, there does not seem to be any reason to think that truth is generally accessible in this strong sense. Therefore, the crucial question is whether it is possible to make rational appraisals that we have made progress in the direction of the truth (see Section 3.4).

A goal is effectively recognizable if there are routine or mechanical tests for showing that the goal has been reached or approached. If the defining criteria of progress are not recognizable in this strong sense, we have to distinguish true or real progress from our perceptions or estimations of progress . In other words, claims of the form ‘The step from stage $A$ to stage $B$ is progressive’ have to be distinguished from our appraisals of the form ‘The step from stage $A$ to stage $B$ seems progressive on the available evidence’. The latter appraisals, as our own judgments, are recognizable, but the former claims may be correct without our knowing it. Characteristics and measures that help us to make such appraisals are then indicators of progress .

Laudan requires that a rational goal for science should be accessible and effectively recognizable (Laudan 1977, 1984a). This requirement, which he uses to rule out truth as a goal of science, is very strong. The demands of rationality cannot dictate that a goal has to be given up, if there are reasonable indicators of progress towards it.

A goal may be backward-looking or forward-looking : it may refer to the starting point or to the destination point of an activity. If my aim is to travel as far from home as possible, my success is measured by my distance from Helsinki. If I wish to become ever better and better piano player, my improvement can be assessed relative to my earlier stages, not to any ideal Perfect Pianist. But if I want to travel to San Francisco, my progress is a function of my distance from the destination. Only in the special case, where there is only one way from $A$ to $B$, the backward-looking and the forward-looking criteria (i.e., distance from $A$ and distance to $B)$ determine each other.

Kuhn and Stegmüller were advocating backward-looking criteria of progress. In arguing against the view that “the proper measure of scientific achievement is the extent to which it brings us closer to ” the ultimate goal of “one full, objective true account of nature,” Kuhn suggested that we should “learn to substitute evolution-from-what-we-know for evolution-toward-what-we-wish-to-know” (Kuhn 1970, p. 171). In the same spirit, Stegmüller (1976) argued that we should reject all variants of “a teleological metaphysics” defining progress in terms of “coming closer and closer to the truth.”

A compromise between forward-looking and backward-looking criteria can be proposed in the following way. If science is viewed as a knowledge-seeking activity, it is natural to define real progress in forward-looking terms: the cognitive aim of science is to know something that is still unknown, and our real progress depends on our distance from this destination. But, as this goal is unknown to us, our estimates or perceptions of progress have to be based on backward-looking evidential considerations. This kind of view of the aims of science does not presuppose the existence of one unique ultimate goal. To use Levi’s words, our goals may be “myopic” rather than “messianic” (Levi 1985): the particular target that we wish to hit in the course of our inquiry has to be redefined “locally,” relative to each cognitive problem situation. Furthermore, in addition to the multiplicity of the possible targets, there may be several roads that lead to the same destination. The forward-looking character of the goals of inquiry does not exclude what Stegmüller calls “progress branching.” This is analogous to the simple fact that we may approach San Francisco from New York along two different ways—via Chicago or St Louis.

Some philosophers use the concepts of progress and rationality as synonyms: progressive steps in science are precisely those that are based upon the scientists’ rational choices. One possible objection is that scientific discoveries are progressive when they introduce novel ideas, even though they cannot be fully explained in rational terms (Popper 1959; cf. Hanson 1958; Kleiner 1993). However, another problem is more relevant here: By whose lights should such steps be evaluated? This question is urgent especially if we acknowledge that standards of good science have changed in history (Laudan 1984a).

As we shall see, the main rival philosophical theories of progress propose absolute criteria, such as problem-solving capacity or increasing truthlikeness, that are applicable to all developments of science throughout its history. On the other hand, rationality is a methodological concept which is historically relative : in assessing the rationality of the choices made by the past scientists, we have to study the aims, standards, methods, alternative theories and available evidence accepted within the scientific community at that time (cf. Doppelt 1983, Laudan 1987; Niiniluoto 1999a). If the scientific community $SC$ at a given point of time $t$ accepted the standards $V$, then the preference of $SC$ for theory $T$ over $T'$ on evidence $e$ was rational just in case the epistemic utility of $T$ relative to $V$ was higher than that of $T'$. But in a new situation, where the standards were different from $V$, a different preference might have been rational.

3. Theories of Scientific Progress

A major controversy among philosophers of science is between instrumentalist and realist views of scientific theories (Leplin 1984; Psillos 1999; Niiniluoto 1999a; Saatsi 2018). The instrumentalists follow Duhem in thinking that theories are merely conceptual tools for classifying, systematizing and predicting observational statements, so that the genuine content of science is not to be found on the level of theories (Duhem 1954). Scientific realists , by contrast, regard theories as attempts to describe reality even beyond the realm of observable things and regularities, so that theories can be regarded as statements having a truth value. Excluding naive realists, most scientists are fallibilists in Peirce’s sense: scientific theories are hypothetical and always corrigible in principle. They may happen to be true, but we cannot know this for certain in any particular case. But even when theories are false, they can be cognitively valuable if they are closer to the truth than their rivals (Popper 1963). Theories should be testable by observational evidence, and success in empirical tests gives inductive confirmation (Hintikka 1968; Kuipers 2000) or non-inductive corroboration to the theory (Popper 1959).

It might seem natural to expect that the main rival accounts of scientific progress would be based upon the positions of instrumentalism and realism. But this is only partly true. To be sure, naive realists as a rule hold the accumulation-of-truths view of progress, and many philosophers combine the realist view of theories with the axiological thesis that truth is an important goal of scientific inquiry. A non-cumulative version of the realist view of progress can be formulated by using the notion of truthlikeness. But there are also philosophers who accept the possibility of a realist treatment of theories, but still deny that truth is a relevant value of science which could have a function in the characterization of scientific progress. Nancy Cartwright et al . (2022) suggest that truth should be replaced by reliability as the ultimate goal of science. Bas van Fraassen’s (1980) constructive empiricism takes the desideratum of science to be empirical adequacy : what a theory says about the observable should be true. The acceptance of a theory involves only the claim that it is empirically adequate, not its truth on the theoretical level. Van Fraassen has not developed an account of scientific progress in terms of his constructive empiricism, but presumably such an account would be close to empiricist notions of reduction and Laudan’s account of problem-solving ability (see Section 3.2).

An instrumentalist who denies that theories have truth values usually defines scientific progress by referring to other virtues theories may have, such as their increasing empirical success. In 1906 Duhem expressed this idea by a simile: scientific progress is like a mounting tide, where waves rise and withdraw, but under this to-and-fro motion there is a slow and constant progress. However, he gave a realist twist to his view by assuming that theories classify experimental laws, and progress means that the proposed classifications approach a “natural classification” (Duhem 1954).

Evolutionary epistemology is open to instrumentalist (Toulmin 1972) and realist (Popper 1972) interpretations (Callebaut and Pinxten 1987; Radnitzky and Bartley 1987). A biological approach to human knowledge naturally gives emphasis to the pragmatist view that theories function as instruments of survival. Darwinist evolution in biology is not goal-directed with a fixed forward-looking goal; rather, species adapt themselves to an ever changing environment. In applying this account to the problem of knowledge-seeking, the fitness of a theory can be taken to mean that the theory is accepted by members of the scientific community. But a realist can reinterpret the evolutionary model by taking fitness to mean the truth or truthlikeness of a theory (Niiniluoto 1984).

For a constructive empiricist, it would be natural to think that among empirically adequate theories one theory $T_{2}$ is better than another theory $T_{1}$ if $T_{2}$ entails more true observational statements than $T_{1}$. Such a comparison makes sense at least if the observation statements entailed by $T_{1}$ are a proper subset of those entailed by $T_{2}$. Kemeny and Oppenheim (1956) gave a similar condition in their definition of reduction: $T_{1}$ is reducible to $T_{2}$ if and only if $T_{2}$ is at least as well systematized as $T_{1}$ and $T_{2}$ is observationally stronger than $T_{1}$, i.e., all observational statements explained by $T_{1}$ are also consequences of $T_{2}$. Variants of such an empirical reduction relation has been given by the structuralist school in terms of set-theoretical structures (Stegmüller 1976; Scheibe 1986; Balzer et al . 1987; Moulines 2000). A similar idea, but applied to cases where the first theory $T_{1}$ has been falsified by some observational evidence, was used by Lakatos in his definition of empirically progressive research programmes: the new superseding theory $T_{2}$ should have corroborated excess content relative to $T_{1}$ and $T_{2}$ should contain all the unrefuted content of $T_{1}$ (Lakatos and Musgrave 1970). The definition of Kuipers (2000) allows that even the new theory $T_{2}$ is empirically refuted: $T_{2}$ should have (in the sense of set-theoretical inclusion) more empirical successes, but fewer empirical counter-examples than $T_{1}$.

Against these cumulative definitions it has been argued that definitions of empirical progress have to take into account an important complication. A new theory often corrects the empirical consequences of the previous one, i.e., $T_{2}$ entails observational statements $e_{2}$ which are in some sense close to the corresponding consequences $e_{1}$ of $T_{1}$. Various models of approximate explanation and approximate reduction have been introduced to handle these situations. An important special case is the limiting correspondence relation: theory $T_{2}$ approaches theory $T_{1}$ (or the observational consequences of $T_{2}$ approach those of $T_{1})$ when some parameter in its laws approaches a limit value (e.g., theory of relativity approaches classical mechanics when the velocity of light c grows without limit). Here $T_{2}$ is said to be a concretization or de-idealization of the idealized theory $T_{1}$ (Nowak 1980; Nowakowa and Nowak 2000; Kuipers 2019). However, these models do not automatically guarantee that the step from an old theory to a new one is progressive. For example, classical mechanics can be related by the correspondence condition to an infinite number of alternative and mutually incompatible theories, and some additional criteria are needed to pick out the best among them.

Kuhn’s (1962) strategy was to avoid the notion of truth and to understand science as an activity of making accurate predictions and solving problems or “puzzles”. Paradigm-based normal science is cumulative in terms of the problems solved, and even paradigm-changes or revolutions are progressive in the sense that “a relatively large part” of the problem-solving capacity of the old theory is preserved in the new paradigm. But, as Kuhn argued, it may happen that some problems solved by the old theory are no longer relevant or meaningful for the new theory. These cases are called “Kuhn-losses.” A more systematic account of these ideas is given by Laudan (1977): the problem-solving effectiveness of a theory is defined by the number and importance of solved empirical problems minus the number and importance of the anomalies and conceptual problems that the theory generates. Here the concept of anomaly refers to a problem that a theory fails to solve, but is solved by some of its rivals. For Laudan the solution of a problem by a theory $T$ means that the “statement of the problem” is deduced from $T$. A good theory is thus empirically adequate, strong in its empirical content, and—Laudan adds—avoids conceptual problems.

One difficulty for the problem-solving account is to find a proper framework for identifying and counting problems (Rescher 1984; Kleiner 1993). When Newton’s mechanics is applied to determine the orbit of the planet Mars, this can be counted as one problem. But, given an initial position of Mars, the same theory entails a solution to an infinite number of questions concerning the position of Mars at time $t$. Perhaps the most important philosophical issue is whether one may consistently hold that the notion of problem-solving may be entirely divorced from truth and falsity: the realist may admit that science is a problem-solving activity, if this means the attempt to find true solutions to predictive and explanatory questions (Popper, 1972; Niiniluoto 1984). Bird’s (2007) main criticism against the “functional account” of Kuhn and Laudan is its consequence that the cumulation of false solutions from an entirely false theory counts as scientific progress (e.g. Oresme in the fourteenth century believed that hot goat’s blood could split diamonds).

According to Shan (2019), “science progresses if more useful research problems and their corresponding solutions are proposed”. Progress means that “more useful exemplary practices are proposed”, where usefulness requires repeatability in further investigation (Shan 2023). This definition involves both problem-defining and problem-solving, as illustrated by the development of early genetics from Darwin to Bateson. Articles in Shan (2023) apply it to economics, seismology, and interdisciplinary sciences. Shan gives up the typical Kuhn-Laudan assumption that the scientific community is able to know whether it makes progress or not, and is open to the introduction of the notions of know-how and perspectival truth, so that his “new functional approach” is a compromise with what Bird (2007) calls the “epistemic view” of progress. Bird (2023) and Dellsén (2023) object that some progressive developments (e.g. the discovery of X-rays, applications of Newtonian mechanics) do not involve the proposal of any new exemplary practices. It can also be argued that improved experimentation and exploration belong to factors which promote but do not constitute progress in science.

A different view of problem-solving is involved in those theories which discuss problems of decision and action . A radical pragmatist view treats science as a systematic method of solving such decision problems relative to various kinds of practical utilities. According to the view called behavioralism by the statistician L J. Savage, science does not produce knowledge, but rather recommendations for actions: to accept a hypothesis is always a decision to act as if that hypothesis were true. Progress in science can then be measured by the achievement of the practical utilities of the decision maker. An alternative methodological version of pragmatism is defended by Rescher (1977) who accepts the realist view of theories with some qualifications, but argues that the progress of science has to be understood as “the increasing success of applications in problem-solving and control.” Similarly, Douglas (2014), after suggesting that the distinction between pure and applied science should be relinquished, defines progress “in terms of the increased capacity to predict, control, manipulate, and intervene in various contexts.” A concrete example of interdisciplinary “frontier science” is given by Nersessian (2022): bioengineering scientists create novel problem-solving methods which help to understand complex dynamical biological systems sufficiently in order to control and intervene in them. Mizrahi (2013) and Shan (2023) count increasing know how as progress in science. But, in this view, the notion of scientific progress is in effect reduced to science-based technological progress (cf. Niiniluoto 1984).

Already the ancient philosophers regarded explanation as an important function of science. The status of explanatory theories was interpreted either in an instrumentalist or realist way: Plato’s school started the tradition of “saving the appearances” in astronomy, while Aristotle took theories to be necessary truths. Both parties can take explanatory power to be a criterion of a good theory, as shown by van Fraassen’s (1980) constructive empiricism and Wilfrid Sellars’ scientific realism (Pitt 1981; Tuomela 1985). When it is added that a good theory should also yield true empirical predictions, the notions of explanatory and predictive power can be combined within the notion of systematic power (Hempel 1965). If the demand of systematic power simply means that a theory has many true deductive consequences in the observational language, this concept is essentially equivalent to the notion of empirical success and empirical problem-solving ability discussed in Section 3.2, but normally explanation is taken to include additional structural conditions besides mere deduction (Aliseda 2006). Inductive systematization should also be taken into account (Hempel 1965; Niiniluoto and Tuomela 1973).

One important idea regarding systematization is that a good theory should unify empirical data and laws from different domains (Kitcher 1993; Schurz 2015). For Whewell, the paradigm case of such “consilience” was the successful unification of Kepler’s laws and Galileo’s laws by means of Newton’s theory.

If theories are underdetermined by observational data, then one is often advised to choose the simplest theory compatible with the evidence (Foster and Martin 1966). Simplicity may be an aesthetic criterion of theory choice (Kuipers 2019), but it may also have a cognitive function in helping us in our attempt to understand the world in an “economical” way. Ernst Mach’s notion of the economy of thought is related to the demand of manageability , which is important especially in the engineering sciences and other applied sciences: for example, a mathematical equation can be made “simpler” by suitable approximations, so that it can be solved by a computer. Simplicity has also been related to the notion of systematic or unifying power. This is clear in Eino Kaila’s concept of relative simplicity , which he defined in 1939 as the ratio between the explanatory power and the structural complexity of a theory (for a translation, see Kaila 2014). According to this conception, progress can be achieved by finding structurally simpler explanations of the same data, or by increasing the scope of explanations without making them more complex. Laudan’s formula of solved empirical problems minus generated conceptual problems is a variation of the same idea.

After Hempel’s pioneering work in 1948, various probabilistic measures of explanatory power have been proposed (Hempel 1965; Hintikka 1968). Most of them demand that the explanatory theory $h$ should be positively relevant to the empirical data $e$. This is the case also with the particular proposal \[ \frac{P(h\mid e) - P(h\mid\neg e)}{P(h\mid e) + P(h\mid\neg e)} \] defended by Schupbach and Sprenger (2011) as the unique measure which satisfies seven intuitively plausible adequacy conditions. Dellsén’s (2016) original version of his noetic account defines progress in terms of increasing explanations and predictions, but he does not apply measures of explanatory or systematic power.

While philosophers from Hempel (1965) to Dellsén (2016) have treated explanation and prediction as equally important for scientific advance, some authors have a strong preference for prediction against the “explanationists”. Following Akaike’s statistical account of model selection, Sober (2008) takes simplicity and predictive accuracy to be the main virtues of a scientific theory. Lakatos emphasized the role of temporally new predictions in his view of progress by research programmes (Lakatos and Musgrave 1970). Leplin (1997) characterizes “novel” predictions by the independence condition, i.e. they were not used in the construction of a theory, and argues that such such novel predictions can be explained only by the truth of the theory (cf. Alai 2014). However, Vickers (2022) argues that evidence provided by novel predictions has been historically unreliable, suggesting that “future-proof science” has to be identified by at least 95 per cent consensus of the scientific community.

Realist theories of scientific progress take truth to be an important goal of inquiry. This view is built into the classical definition of knowledge as justified true belief: if science is a knowledge-seeking activity, then it is also a truth-seeking activity. However, truth cannot be the only relevant epistemic utility of inquiry. This is shown in a clear way by cognitive decision theory (Levi 1967; Niiniluoto 1987).

Let us denote by $B = \{h_{1}, \ldots ,h_{n}\}$ a set of mutually exclusive and jointly exhaustive hypotheses. Here the hypotheses in $B$ may be the most informative descriptions of alternative states of affairs or possible worlds within a conceptual framework $L$. For example, they may be complete theories expressible in a finite first-order language. If $L$ is interpreted on a domain $U$, so that each sentence of $L$ has a truth value (true or false), it follows that there is one and only one true hypothesis (say $h^*$) in $B$. Our cognitive problem is to identify the target $h^*$ in $B$. The elements $h_{i}$ of $B$ are the (potential) complete answers to the problem. The set $D(B)$ of partial answers consists of all non-empty disjunctions of complete answers. The trivial partial answer in $D(B)$, corresponding to ‘I don’t know’, is represented by a tautology, i.e., the disjunction of all complete answers.

For any $g$ in $D(B)$, we let $u(g, h_{j})$ be the epistemic utility of accepting $g$ if $h_{j}$ is true. We also assume that a rational probability measure $P$ is associated with language $L$, so that each $h_{j}$ can be assigned with its epistemic probability $P(h_{j}\mid e)$ given evidence $e$. Then the best hypothesis in $D(B)$ is the one $g$ which maximizes the expected epistemic utility

For comparative purposes, we may say that one hypothesis is better than another if it has a higher expected utility than the other by formula (1).

If truth is the only relevant epistemic utility, all true answers are equally good and all false answers are equally bad. Then we may take $u(g, h_{j})$ simply to be the truth value of $g$ relative to $h_{j}$:

Hence, $u(g, h^*)$ is the real truth value $tv(g)$ of $g$ relative to the domain $U$. It follows from (1) that the expected utility $U(g\mid e)$ equals the posterior probability $P(g\mid e)$ of $g$ on $e$. In this sense, we may say that posterior probability equals expected truth value. The rule of maximizing expected utility leads now to an extremely conservative policy: the best hypotheses $g$ on $e$ are those that satisfy $P(g\mid e) = 1$, i.e., are completely certain on $e$ (e.g. $e$ itself, logical consequences of $e$, and tautologies). On this account, if we are not certain of the truth, then it is always progressive to change an uncertain answer to a logically weaker one.

The argument against using high probability as a criterion of theory choice was made already by Popper in 1934 (see Popper 1959). He proposed that good theories should be bold or improbable. This idea has been made precise in the theory of semantic information.

Levi (1967) measures the information content $I(g)$ of a partial answer $g$ in $D(B)$ by the number of complete answers it excludes. With a suitable normalization, $I(g) = 1$ if and only if $g$ is one of the complete answers $h_{j}$ in $B$, and $I(g) = 0$ for a tautology. If we now choose $u(g, h_{j}) = I(g)$, then $U(g\mid e) = I(g)$, so that all the complete answers in B have the same maximal expected utility 1. This measure favors strong hypotheses, but it is unable to discriminate between the strongest ones. For example, the step from a false complete answer to the true one does not count as progress. Therefore, information cannot be the only relevant epistemic utility.

Another measure of information content is $cont(g) = 1 - P(g)$ (Hintikka 1968). If we choose $u(g, h_{j}) = cont(g)$, then the expected utility $U(g\mid e) = 1 - P(g)$ is maximized by a contradiction, as the probability of a contradictory sentence is zero. Any false theory can be improved by adding new falsities to it. Again we see that information content alone does not give a good definition of scientific progress. The same remark can be made about explanatory and systematic power.

Levi’s (1967) proposal for epistemic utility is the weighted combination of the truth value $tv(g)$ of $g$ and the information content $I(g)$ of $g$:

where $0 \lt a \lt \bfrac{1}{2}$ is an “index of boldness,” indicating how much the scientist is willing to risk error, or to “gamble with truth,” in her attempt to be relieved from agnosticism. The expected epistemic utility of $g$ is then

A comparative notion of progress ‘$g_{1}$ is better than $g_{2}$’ could be defined by requiring that both $I(g_{1}) \gt I(g_{2})$ and $P(g_{1}\mid e) \gt P(g_{2}\mid e)$, but most hypotheses would be incomparable by this requirement. By using the weight $a$, formula (3) expresses a balance between two mutually conflicting goals of inquiry. It has the virtue that all partial answers $g$ in $D(B)$ are comparable with each other: $g$ is better than $g'$ if and only if the value of (3) is larger for $g$ than for $g'$.

If epistemic utility is defined by information content cont(g) in a truth-dependent way, so that

(i,e., in accepting hypothesis $g$, we gain the content of $g$ if $g$ is true, but we lose the content of the true hypothesis $\neg g$ if $g$ is false), then the expected utility $U(g\mid e)$ is equal to

This measure combines the criteria of boldness (small prior probability $P(g))$ and high posterior probability $P(g\mid e)$. Similar results can be obtained if $cont(g)$ is replaced by Hempel’s (1965) measure of systematic power $syst(g, e) = P(\neg g\mid \neg e)$.

For Levi, the best hypothesis in $D(B)$ is the complete true answer. But his utility assignment also makes assumptions that may seem problematic: all false hypotheses (even those that make a very small error) are worse than all truths (even the uninformative tautology); all false complete answers have the same utility (see, however, the modified definition in Levi, 1980); among false hypotheses utility covaries with logical strength (i.e. if $h$ and $h'$ are false and $h$ entails $h'$, then $h$ has greater utility than $h')$. These features are motivated by Levi’s project of using epistemic utility as a basis of acceptance rules. But if such utilities are used for ordering rival theories, then the theory of truthlikeness suggests other kinds of principles.

Popper’s notion of truthlikeness is also a combination of truth and information (Popper 1963, 1972). For him, verisimilitude represents the idea of “approaching comprehensive truth.” Popper’s explication used the cumulative idea that the more truthlike theory should have (in the sense of set-theoretical inclusion) more true consequences and less false consequences, but it turned out that this comparison is not applicable to pairs of false theories. An alternative method of defining verisimilitude, initiated in 1974 by Pavel Tichy and Risto Hilpinen, relies essentially on the concept of similarity.

In the similarity approach, as developed in Niiniluoto (1987), closeness to the truth is explicated “locally” by means of the distances of partial answers $g$ in $D(B)$ to the target $h^*$ in a cognitive problem $B$. For this purpose, we need a function $d$ which expresses the distance $d(h_{i}, h_{j}) =: d_{ij}$ between two arbitrary elements of $B$. By normalization, we may choose $0 \le d_{ij} \le 1$. The choice of $d$ depends on the cognitive problem $B$, and makes use of the metric structure of $B$ (e.g., if $B$ is a subspace of the real numbers $\Re)$ or the syntactic similarity between the statements in $B$. Then, for a partial answer $g$, we let $D_{\min}(h_{i}, g)$ be the minimum distance of the disjuncts in $g$ from $h_{i}$, and $D_{\rmsum}(h_{i}, g)$ the normalized sum of the distances of the disjuncts of $g$ from $h_{i}$. Then $D_{\min}(h_{i}, g)$ tells how close to $h_{i}$ hypothesis $g$ is, so that the degree of approximate truth of $g$ (relative to the target $h^*$) is $1 - D_{\min}(h^*, g)$. On the other hand, $D_{\rmsum}(h_{i}, g)$ includes a penalty for all the mistakes that $g$ allows relative to $h_{i}$. The min-sum measure

where $a \gt 0$ and $b \gt 0$, and $(a + b)\le 1$, combines these two aspects. Then the degree of truthlikeness of $g$ is

Thus, parameter $a$ indicates our cognitive interest in hitting close to the truth, and parameter $b$ indicates our interest in excluding falsities that are distant from the truth. In many applications, choosing $a$ to be equal to $2b$ gives intuitively reasonable results.

If the distance function $d$ on $B$ is trivial, i.e., $d_{ij} = 1$ if and only if $i = j$, and otherwise 0, then $Tr(g, h^*)$ reduces to the variant (2) of Levi’s definition of epistemic utility.

Obviously $Tr(g, h^*)$ takes its maximum value 1 if and only if $g$ is equivalent to $h^*$. If $g$ is a tautology, i.e., the disjunction of all elements $h_{i}$ of $B$, then $Tr(g,h^*) = 1 - b$. If $Tr(g, h^*) \lt 1 - b$, $g$ is misleading in the strong sense that its cognitive value is smaller than that of complete ignorance.

Oddie (1986) has continued to favor the average function instead of the min-sum measure (cf. Oddie and Cevolani 2022). An alternative account of truth approximation is given by Kuipers (2019).

When $h^*$ is unknown, the degree of truthlikeness (6) cannot be calculated. But the expected degree of verisimilitude of a partial answer $g$ given evidence $e$ is given by

If evidence $e$ entails some $h_{j}$ in $B$, or makes $h_{j}$ completely certain (i.e., $P(h_{j}\mid e) = 1)$, then $ver(g\mid e)$ reduces to $Tr(g,h_{j})$. If all the complete answers $h_{i}$ in $B$ are equally probable on $e$, then $ver(h_{i}\mid e)$ is also constant for all $h_{i}$.

The truthlikeness function $Tr$ allows us to define an absolute concept of real progress :

(RP) Step from $g$ to $g'$ is progressive if and only if $Tr(g, h^*) \lt Tr(g', h^*)$,

and the expected truthlikeness function $ver$ gives the relative concept of estimated progress :

(EP) Step from $g$ to $g'$ seems progressive on evidence $e$ if and only if $ver(g\mid e) \lt ver(g'\mid e)$.

(Cf. Niiniluoto 1980.) According to definition RP, it is meaningful to say that one theory $g'$ satisfies better the cognitive goal of answering problem $B$ than another theory $g$. This is an absolute standard of scientific progress in the sense of Section 2.5. Definition EP shows how claims of progress can be fallibly evaluated on the basis of evidence: if $ver(g\mid e) \lt ver(g'\mid e)$, it is rational to claim on evidence $e$ that the step from $g$ to $g'$ in fact is progressive. This claim may of course be mistaken, since estimation of progress is relative to two factors: the available evidence $e$ and the probability measure $P$ employed in the definition of $ver$. Both evidence $e$ and the epistemic probabilities $P(h_{i}\mid e)$ may mislead us. In this sense, the problem of estimating verisimilitude is as difficult as the problem of induction.

Rowbottom (2015) argues against RP and EP that scientific progress is possible in the absence of increasing verisimilitude. He asks us to imagine that the scientists in a specific area of physics have found the maximally truthlike theory C*. Yet this general true theory could be used for further predictions and applications. This is indeed the case if we do not make the idealized assumption that the scientists know all the logical consequences of their theories. Then the predictions from C* constitute new cognitive problems. Moreover, in Rowbottom’s thought experiment further progress is possible by expanding the conceptual framework in order to consider as a target a deeper truth than C* (Niiniluoto 2017). A similar reply can be given to Dellsén (2023), who argues that Newton’s explanation of Kepler’s laws of planetary motions does not constitute progress on the truthlikeness account, since the theory and the laws were already accepted before the explanation: Newton was successful in solving the cognitive problem “Which theory would explain Kepler’s laws?”.

The measure of expected truthlikeness can be used for retrospective comparisons of past theories $g$, if evidence $e$ is taken to include our currently accepted theory $T$, i.e., the truthlikeness of $g$ is estimated by $ver(g\mid e \amp T)$ (Niiniluoto 1984, 171). In the same spirit, Barrett (2008) has proposed that—assuming that science makes progress toward the truth through the elimination of descriptive error—the “probable approximate truth” of Newtonian gravitation can be warranted by its “nesting relations” to the General Theory of Relativity.

The definition of progress by RP can be contrasted with the model of belief revision (Gärdenfors 1988). The simplest case of revision is expansion: a theory $T$ is conjoined by an input statement $A$, so that the new theory is $T \amp A$. According to the min-sum measure, if $T$ and $A$ are true, then the expansion $T \amp A$ is at least as truthlike as $T$. But if $T$ is false and $A$ is true, then $T \amp A$ may be less truthlike than $T$. For example, let the false theory $T$ state that the number of planets is 9 or 20, and let $A$ be the true sentence that this number is 8 or 20. Then $T \amp A$ states that the number of planets is 20, but this is clearly less truthlike than $T$ itself. Similar examples show that the AGM revision of a false theory by true input need not increase truthlikeness (Niiniluoto 2011).

Bird (2007) has defended the epistemic definition of progress (accumulation of knowledge) against the semantic conception (accumulation of true beliefs or succession of theories with increasing verisimilitude) (see also Bird 2022, 2023). Here knowledge is not defined as justified true belief, but still it is taken to entail truth and justification, so that Bird’s epistemic view in fact returns to the old cumulative model of progress. According to Bird, an accidentally true or truthlike belief reached by irrational methods without any justification does not constitute progress. This kind of thought experiment may seem artificial, since there is always some sort of justification for any hypothetical theory which is accepted or at least seriously considered by the scientific community. But Bird’s argument raises the important question whether justification is merely instrumental for progress (Rowbottom 2008) or necessary for progress (Bird 2008). Another interesting question is whether the rejection of unfounded but accidentally true beliefs is regressive. The truthlikeness approach replies to these problems by distinguishing real progress RP and estimated progress EP: justification is not constitutive of progress in the sense of RP, but claims of real progress can be justified by appealing to expected verisimilitude (Cevolani and Tambolo 2013). On the other hand, the notion of progress explicated by EP (or by the combination of RP and EP) is relative to evidence and justification but at the same time non-cumulative.

Bird (2015) can reformulate his initial example by assuming that an accidentally true or truthlike theory $H$ has been obtained by scientific but yet unreliable means, perhaps by derivation from an accepted theory which turns out to be false. Does such application of mistaken reasoning constitute progress? The interplay of RP and EP allows several possibilities here. Later evidence might show that the initial estimate $ver(H\mid e)$ was too high. Or the Tr-value was in fact high but initially the ver-value was low (e.g. Aristarchus on heliocentric system, Wegener on continental drift) and only later it was increased by new evidence.

Most accounts of truthlikeness satisfy the principle that among true theories truthlikeness covaries with logical strength (for an exception, see Oddie 1986). So accumulation of knowledge is a special case of increasing verisimilitude, but it does not cover the case of progress by successive false theories. In his attempt to rehabilitate the cumulative knowledge model of scientific progress, Bird admits that there are historical sequences of theories none of which are “fully true” (e.g. Ptolemy—Copernicus—Kepler or Galileo—Newton—Einstein). As knowledge entails truth, Bird tries to save his epistemic account by reformulating past false theories as true ones. He proposes that if $g$ is approximately true, then the proposition “approximately $g$” is true, so that “the improving precision of approximations can be an object of knowledge”. One problem with this treatment is that scientists typically formulate their theories as exact statements, and at the time of their proposal it is not known how large margins of errors would be needed to transform them into true theories. With reference to Barrett (2008), Saatsi (2019) argues that the approximate truth of Newtonian mechanics can be assessed only from the vantage point of General Theory of Relativity, so that this knowledge was not epistemically accessible to Newton at his time. Further, many past theories were radically false rather than approximately true or truthlike, but still they could be improved by more truthlike successors. Ptolemy’s geocentric theory was rejected in the Copernican revolution, not retained in the form “approximately Ptolemy”. Indeed, the progressive steps from Ptolemy to Copernicus or from Newton to Einstein are not only matters of improved precision but involve changes in theoretical postulates and laws. A further problem for Bird’s proposal is the question whether his approximation propositions are able to distinguish between progress and regress in science (Niiniluoto 2014).

Dellsén (2016, 2018b) has formulated the noetic account of scientific progress as increasing understanding. Using objectual understanding instead of understanding-why, he characterizes understanding in terms of “grasping how to correctly explain and predict aspects of a given target”. Against Bird (2007), who takes understanding to be a species of knowledge of causes, Dellsén argues that understanding does not require the scientists to have justification for, or even belief in, the explanations or predictions they propose. Still, understanding is a matter of degree. Thus, there are increases in scientific understanding without accumulation of scientific knowledge (e.g. Einstein’s explanation of Brownian motion in terms of the kinetic theory of heat) and accumulation of scientific knowledge without increases in understanding (e.g. knowledge about random experimental outcomes or spurious statistical correlations). The latter thesis is easy to accept, especially if explanation needs laws, but on the other hand the epistemic and truthlikeness approaches could agree against Dellsénthat the collection of new important data may constitute scientific progress; Bird’s (2023) example is the activity of cataloguing stars. The possibility of “quasi-factive” understanding by means of idealized theories (a common feature with the verisimilitudinarian approach) is taken to be an advantage of the noetic account. Park (2017) has challenged Dellsén’s conclusions against the epistemic definition. He argues that scientific understanding involves beliefs that the explained phenomena are real and the confirmed predictions are true. He also argues that Wegener’s continental drift theory, which was not supported by available evidence, was progressive, since it paved the way for the later theory of plate tectonics in the 1960s. Dellsén (2018a) questions Park’s arguments by rejecting the “means-end thesis”, i.e., one should make the crucial distinction between cognitive and non-cognitive scientific progress and likewise distinguish episodes that constitute and promote scientific progress.

Dellsén (2023) has restated his noetic account by characterizing understanding in terms of dependency relations (causation, constitution, and grounding). The requirement that a grasped dependency model should be sufficiently accurate and comprehensive brings his account close to the Popperian notion of truthlikeness as a combination of truth and information (cf. Section 3.5). Bird (2023) objects that the discovery of X-rays in 1895 did not involve dependency relations. Dellsén’s (2023) additional proposal to analyze understanding among those for whom scientific progress is made, instead of those by whom progress is achieved, is problematic, since the transmission of public scientific information to non-scientists (such as students, engineers, medical professionals, and policy-makers) is an important consequence of inquiry without constituting cognitive scientific progress.

The lively debate about four current accounts of scientific progress is continued in Shan (2023): epistemic (Bird), semantic (Niiniluoto), functional (Shan), and noetic (Dellsén) (see also Rowbottom 2023).

In Section 3.5., we made a distinction between real and estimated progress in terms of the truthlikeness measures. A similar distinction can be made in connection with measures of empirical success. For example, one may distinguish two notions of the problem-solving ability of a theory: the number of problems solved so far , and the number of solvable problems. Real progress could be defined by the latter, while the former gives us an estimate of progress.

The scientific realist may continue this line of thought by arguing that all measures of empirical success in fact are at best indicators of real cognitive progress, measured in terms of truth or truthlikeness. For example, if $T$ explains $e$, then it can be shown that $e$ also confirms $T$, or increases the probability of $T$ (Niiniluoto 1999b). A similar reasoning can be employed to give the so-called “ultimate argument” or “no miracle argument” for scientific realism: theoretical realism is the only assumption that does not make the empirical success of science a miracle (Putnam, 1978; Psillos 1999; Alai 2014; Niiniluoto 2017; Kuipers 2019; cf. criticism in Laudan 1984b). This means that the best explanation of the empirical progress of science is the hypothesis that science is also progressive on the level of theories.

The thesis that science is progressive is an overall claim about scientific activities. It does not imply that each particular step in science has in fact been progressive: individual scientists make mistakes, and even the scientific community is fallible in its collective judgments. For this reason, we should not propose such a definition that the thesis about the progressive nature of science becomes a tautology or an analytic truth. This undesirable consequence follows if we define truth as the limit of scientific inquiry (this is sometimes called the consensus theory of truth), as then it is a mere tautology that the limit of scientific research is the truth (Laudan 1984a). But this “trivialization of the self-corrective thesis” cannot be attributed to Peirce who realized that truth and the limit of inquiry coincide at best with probability one (Niiniluoto 1980). The notion of truthlikeness allows us to make sense of the claim that science converges towards the truth. But the characterization of progress as increasing truthlikeness, given in Section 3.5, does not presuppose “teleological metaphysics” (Stegmüller 1976), “convergent realism” (Laudan 1984), or “scientific eschatology” (Moulines 2000), as it does not rely on any assumption about the future behavior of science.

The claim about scientific progress can still be questioned by the theses that observations and ontologies are relative to theories. If this is true, the comparison of rival theories appears to be impossible on cognitive or rational grounds. Kuhn (1962) compared paradigm-changes to Gestalt switches (Dilworth 1981). Feyerabend (1984) concluded from his methodological anarchism that the development of science and art resemble each other.

Hanson, Popper, Kuhn, and Feyerabend agreed that all observation is theory-laden , so that there is no theory-neutral observational language. Accounts of reduction and progress, which take for granted the preservation of some observational statements within theory-change, thus run into troubles. Even though Laudan’s account of progress allows Kuhn-losses, it can be argued that the comparison of the problem-solving capacity of two rival theories presupposes some kind of correlation or translation between the statements of these theories (Pearce 1987). Various replies have been proposed to this issue. One is the movement from language to structures (Stegmüller 1976; Moulines 2000), but it turns out that a reduction on the level structures already guarantees commensurability, since it induces a translation between conceptual frameworks (Pearce 1987). Another has been the point that an evidence statement $e$ may happen to be neutral with respect to rival theories $T_{1}$ and $T_{2}$, even though it is laden with some other theories. The realist may also point that the theory-ladenness of observations concerns at most the estimation of progress (EP), but the definition of real progress (RP) as increasing truthlikeness does not mention the notion of observation at all.

Even though Popper accepted the theory-ladenness of observations, he rejected the more general thesis about incommensurability as “the myth of the framework” (Lakatos and Musgrave 1970). Popper insisted that the growth of knowledge is always revolutionary in the sense that the new theory contradicts the old one by correcting it, but there is still continuity in theory-change, as the new theory should explain why the old theory was successful to some extent. Feyerabend tried to claim that successive theories are both inconsistent and incommensurable with each other, but this combination makes little sense. Kuhn argued against the possibility of finding complete translations between the languages of rival theories, but in his later work he admitted the possibility that a scientist may learn different theoretical languages (Hoyningen-Huene 1993). Kuhn kept insisting that there is “no theory-independent way to reconstruct phrases like ‘really there’,” i.e., each theory has its own ontology. Convergence to the truth seems to be impossible, if ontologies change with theories. The same idea has been formulated by Putnam (1978) and Laudan (1984a) in the so-called “pessimistic meta-induction”: as many past theories in science have turned out to be non-referring, there is all reason to expect that even the future theories fail to refer—and thus also fail to be approximately true or truthlike. But the optimistic reply by comparative realists points out that for all rejected theories in Laudan’s list the scientists have been able to find a better, more truthlike alternative (Niiniluoto 2017; Kuipers 2019).

The difficulties for realism seem to be reinforced by the observation that measures of truthlikeness are relative to languages. The choice of conceptual frameworks cannot be decided by means of the notion of truthlikeness, but needs additional criteria. In defense of the truthlikeness approach, one may point to the fact that the comparison of two theories is relevant only in those cases where they are considered (perhaps via a suitable translation) as rival answers to the same cognitive problem. It is interesting to compare Newton’s and Einstein’s theories for their truthlikeness, but not Newton’s and Darwin’s theories. When definitions RP and EP are applied to rival theories in different languages, they have to be translated into a common conceptual framework.

Another line is to appeal to theories of reference in order to show that rival theories can after all be regarded as speaking about the same entities (Psillos 1999). For example, Thompson, Bohr, and later physicists are talking about the same electrons, even though their theories of the electron differ from each other. This is not possible on the standard descriptive theory of reference: a theory $T$ can only refer to entities about which it gives a true description. Kuhn’s and Feyerabend’s meaning holism, with devastating consequences for realism, presupposes this account of reference. A similar argument is used by Moulines (2000), who denies that progress could be understood as “knowing more about the same,” but his own structuralist reconstruction of progress with “partial incommensurability” assumes that rival theories share some intended applications. Causal theories of reference allow that reference is preserved even within changes of theories (Kitcher 1993). The same result is obtained if the descriptive account is modified by introducing a Principle of Charity (Putnam 1975; Smith 1981; Niiniluoto 1999a): a theory refers to those entities about which it gives the most truthlike description. An alternative account, illustrated by the relation of phlogiston theory and oxygen theory, is given by Schurz (2011) by his notion of structural correspondence. This makes it possible that even false theories are referring. Moreover, there can be reference invariance between two successive theories, even though both of them are false; progress means then that the latter theory gives a more truthlike description about their common domain than the old theory.

A radically different account of scientific change emerges from Chang’s (2022) pluralist ontology. Inspired by classical pragmatists, he advocates a charitable definition of reality and truth in terms of “operational coherence”. For example, phlogiston had some succesful applications, so it has some reality, and likewise for oxygen. More generally, Chang defends “conservationist pluralim”: scientists do not tend to discard useful theories from the past, so that scientific progress is largely cumulative. This return to the cumulative model of progress resembles the surprising position that Feyerabend reached from his methodological anarchism without Popperian falsification: “knowledge … is not a gradual approach to the truth. It is rather an ever increasing ocean of mutually incompatible (and perhaps even incommensurable) alternatives … Nothing is ever settled, no view can ever be omitted from the comprehensive account” (Feyerabend 1975 [1993], 21).

Finally, Rowbottom (2023) has advanced meta-normative relativism to challenge claims about scientific progress: inspired by J. L. Mackie’s error-theory in meta-ethics, he argues against the assumption that there are objective or privileged intersubjective aims of science (cf. Section 2.2). Rowbottom allows that individual scientists and groups may have cognitive aims, but doubts attempts to analyze aims on the collective level. His thesis that standards of good science are “ultimately subjective” is in conflict with the fact that science is a social institution, so that the members of the scientific community are jointly committed to methods and values which also characterize standards of scientific progress (Niiniluoto 2020).

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v.25(3); 2014 Oct

Peer Review in Scientific Publications: Benefits, Critiques, & A Survival Guide

Jacalyn kelly.

1 Clinical Biochemistry, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada

Tara Sadeghieh

Khosrow adeli.

2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada

3 Chair, Communications and Publications Division (CPD), International Federation for Sick Clinical Chemistry (IFCC), Milan, Italy

The authors declare no conflicts of interest regarding publication of this article.

Peer review has been defined as a process of subjecting an author’s scholarly work, research or ideas to the scrutiny of others who are experts in the same field. It functions to encourage authors to meet the accepted high standards of their discipline and to control the dissemination of research data to ensure that unwarranted claims, unacceptable interpretations or personal views are not published without prior expert review. Despite its wide-spread use by most journals, the peer review process has also been widely criticised due to the slowness of the process to publish new findings and due to perceived bias by the editors and/or reviewers. Within the scientific community, peer review has become an essential component of the academic writing process. It helps ensure that papers published in scientific journals answer meaningful research questions and draw accurate conclusions based on professionally executed experimentation. Submission of low quality manuscripts has become increasingly prevalent, and peer review acts as a filter to prevent this work from reaching the scientific community. The major advantage of a peer review process is that peer-reviewed articles provide a trusted form of scientific communication. Since scientific knowledge is cumulative and builds on itself, this trust is particularly important. Despite the positive impacts of peer review, critics argue that the peer review process stifles innovation in experimentation, and acts as a poor screen against plagiarism. Despite its downfalls, there has not yet been a foolproof system developed to take the place of peer review, however, researchers have been looking into electronic means of improving the peer review process. Unfortunately, the recent explosion in online only/electronic journals has led to mass publication of a large number of scientific articles with little or no peer review. This poses significant risk to advances in scientific knowledge and its future potential. The current article summarizes the peer review process, highlights the pros and cons associated with different types of peer review, and describes new methods for improving peer review.

WHAT IS PEER REVIEW AND WHAT IS ITS PURPOSE?

Peer Review is defined as “a process of subjecting an author’s scholarly work, research or ideas to the scrutiny of others who are experts in the same field” ( 1 ). Peer review is intended to serve two primary purposes. Firstly, it acts as a filter to ensure that only high quality research is published, especially in reputable journals, by determining the validity, significance and originality of the study. Secondly, peer review is intended to improve the quality of manuscripts that are deemed suitable for publication. Peer reviewers provide suggestions to authors on how to improve the quality of their manuscripts, and also identify any errors that need correcting before publication.

HISTORY OF PEER REVIEW

The concept of peer review was developed long before the scholarly journal. In fact, the peer review process is thought to have been used as a method of evaluating written work since ancient Greece ( 2 ). The peer review process was first described by a physician named Ishaq bin Ali al-Rahwi of Syria, who lived from 854-931 CE, in his book Ethics of the Physician ( 2 ). There, he stated that physicians must take notes describing the state of their patients’ medical conditions upon each visit. Following treatment, the notes were scrutinized by a local medical council to determine whether the physician had met the required standards of medical care. If the medical council deemed that the appropriate standards were not met, the physician in question could receive a lawsuit from the maltreated patient ( 2 ).

The invention of the printing press in 1453 allowed written documents to be distributed to the general public ( 3 ). At this time, it became more important to regulate the quality of the written material that became publicly available, and editing by peers increased in prevalence. In 1620, Francis Bacon wrote the work Novum Organum, where he described what eventually became known as the first universal method for generating and assessing new science ( 3 ). His work was instrumental in shaping the Scientific Method ( 3 ). In 1665, the French Journal des sçavans and the English Philosophical Transactions of the Royal Society were the first scientific journals to systematically publish research results ( 4 ). Philosophical Transactions of the Royal Society is thought to be the first journal to formalize the peer review process in 1665 ( 5 ), however, it is important to note that peer review was initially introduced to help editors decide which manuscripts to publish in their journals, and at that time it did not serve to ensure the validity of the research ( 6 ). It did not take long for the peer review process to evolve, and shortly thereafter papers were distributed to reviewers with the intent of authenticating the integrity of the research study before publication. The Royal Society of Edinburgh adhered to the following peer review process, published in their Medical Essays and Observations in 1731: “Memoirs sent by correspondence are distributed according to the subject matter to those members who are most versed in these matters. The report of their identity is not known to the author.” ( 7 ). The Royal Society of London adopted this review procedure in 1752 and developed the “Committee on Papers” to review manuscripts before they were published in Philosophical Transactions ( 6 ).

Peer review in the systematized and institutionalized form has developed immensely since the Second World War, at least partly due to the large increase in scientific research during this period ( 7 ). It is now used not only to ensure that a scientific manuscript is experimentally and ethically sound, but also to determine which papers sufficiently meet the journal’s standards of quality and originality before publication. Peer review is now standard practice by most credible scientific journals, and is an essential part of determining the credibility and quality of work submitted.

IMPACT OF THE PEER REVIEW PROCESS

Peer review has become the foundation of the scholarly publication system because it effectively subjects an author’s work to the scrutiny of other experts in the field. Thus, it encourages authors to strive to produce high quality research that will advance the field. Peer review also supports and maintains integrity and authenticity in the advancement of science. A scientific hypothesis or statement is generally not accepted by the academic community unless it has been published in a peer-reviewed journal ( 8 ). The Institute for Scientific Information ( ISI ) only considers journals that are peer-reviewed as candidates to receive Impact Factors. Peer review is a well-established process which has been a formal part of scientific communication for over 300 years.

OVERVIEW OF THE PEER REVIEW PROCESS

The peer review process begins when a scientist completes a research study and writes a manuscript that describes the purpose, experimental design, results, and conclusions of the study. The scientist then submits this paper to a suitable journal that specializes in a relevant research field, a step referred to as pre-submission. The editors of the journal will review the paper to ensure that the subject matter is in line with that of the journal, and that it fits with the editorial platform. Very few papers pass this initial evaluation. If the journal editors feel the paper sufficiently meets these requirements and is written by a credible source, they will send the paper to accomplished researchers in the field for a formal peer review. Peer reviewers are also known as referees (this process is summarized in Figure 1 ). The role of the editor is to select the most appropriate manuscripts for the journal, and to implement and monitor the peer review process. Editors must ensure that peer reviews are conducted fairly, and in an effective and timely manner. They must also ensure that there are no conflicts of interest involved in the peer review process.

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Overview of the review process

When a reviewer is provided with a paper, he or she reads it carefully and scrutinizes it to evaluate the validity of the science, the quality of the experimental design, and the appropriateness of the methods used. The reviewer also assesses the significance of the research, and judges whether the work will contribute to advancement in the field by evaluating the importance of the findings, and determining the originality of the research. Additionally, reviewers identify any scientific errors and references that are missing or incorrect. Peer reviewers give recommendations to the editor regarding whether the paper should be accepted, rejected, or improved before publication in the journal. The editor will mediate author-referee discussion in order to clarify the priority of certain referee requests, suggest areas that can be strengthened, and overrule reviewer recommendations that are beyond the study’s scope ( 9 ). If the paper is accepted, as per suggestion by the peer reviewer, the paper goes into the production stage, where it is tweaked and formatted by the editors, and finally published in the scientific journal. An overview of the review process is presented in Figure 1 .

WHO CONDUCTS REVIEWS?

Peer reviews are conducted by scientific experts with specialized knowledge on the content of the manuscript, as well as by scientists with a more general knowledge base. Peer reviewers can be anyone who has competence and expertise in the subject areas that the journal covers. Reviewers can range from young and up-and-coming researchers to old masters in the field. Often, the young reviewers are the most responsive and deliver the best quality reviews, though this is not always the case. On average, a reviewer will conduct approximately eight reviews per year, according to a study on peer review by the Publishing Research Consortium (PRC) ( 7 ). Journals will often have a pool of reviewers with diverse backgrounds to allow for many different perspectives. They will also keep a rather large reviewer bank, so that reviewers do not get burnt out, overwhelmed or time constrained from reviewing multiple articles simultaneously.

WHY DO REVIEWERS REVIEW?

Referees are typically not paid to conduct peer reviews and the process takes considerable effort, so the question is raised as to what incentive referees have to review at all. Some feel an academic duty to perform reviews, and are of the mentality that if their peers are expected to review their papers, then they should review the work of their peers as well. Reviewers may also have personal contacts with editors, and may want to assist as much as possible. Others review to keep up-to-date with the latest developments in their field, and reading new scientific papers is an effective way to do so. Some scientists use peer review as an opportunity to advance their own research as it stimulates new ideas and allows them to read about new experimental techniques. Other reviewers are keen on building associations with prestigious journals and editors and becoming part of their community, as sometimes reviewers who show dedication to the journal are later hired as editors. Some scientists see peer review as a chance to become aware of the latest research before their peers, and thus be first to develop new insights from the material. Finally, in terms of career development, peer reviewing can be desirable as it is often noted on one’s resume or CV. Many institutions consider a researcher’s involvement in peer review when assessing their performance for promotions ( 11 ). Peer reviewing can also be an effective way for a scientist to show their superiors that they are committed to their scientific field ( 5 ).

ARE REVIEWERS KEEN TO REVIEW?

A 2009 international survey of 4000 peer reviewers conducted by the charity Sense About Science at the British Science Festival at the University of Surrey, found that 90% of reviewers were keen to peer review ( 12 ). One third of respondents to the survey said they were happy to review up to five papers per year, and an additional one third of respondents were happy to review up to ten.

HOW LONG DOES IT TAKE TO REVIEW ONE PAPER?

On average, it takes approximately six hours to review one paper ( 12 ), however, this number may vary greatly depending on the content of the paper and the nature of the peer reviewer. One in every 100 participants in the “Sense About Science” survey claims to have taken more than 100 hours to review their last paper ( 12 ).

HOW TO DETERMINE IF A JOURNAL IS PEER REVIEWED

Ulrichsweb is a directory that provides information on over 300,000 periodicals, including information regarding which journals are peer reviewed ( 13 ). After logging into the system using an institutional login (eg. from the University of Toronto), search terms, journal titles or ISSN numbers can be entered into the search bar. The database provides the title, publisher, and country of origin of the journal, and indicates whether the journal is still actively publishing. The black book symbol (labelled ‘refereed’) reveals that the journal is peer reviewed.

THE EVALUATION CRITERIA FOR PEER REVIEW OF SCIENTIFIC PAPERS

As previously mentioned, when a reviewer receives a scientific manuscript, he/she will first determine if the subject matter is well suited for the content of the journal. The reviewer will then consider whether the research question is important and original, a process which may be aided by a literature scan of review articles.

Scientific papers submitted for peer review usually follow a specific structure that begins with the title, followed by the abstract, introduction, methodology, results, discussion, conclusions, and references. The title must be descriptive and include the concept and organism investigated, and potentially the variable manipulated and the systems used in the study. The peer reviewer evaluates if the title is descriptive enough, and ensures that it is clear and concise. A study by the National Association of Realtors (NAR) published by the Oxford University Press in 2006 indicated that the title of a manuscript plays a significant role in determining reader interest, as 72% of respondents said they could usually judge whether an article will be of interest to them based on the title and the author, while 13% of respondents claimed to always be able to do so ( 14 ).

The abstract is a summary of the paper, which briefly mentions the background or purpose, methods, key results, and major conclusions of the study. The peer reviewer assesses whether the abstract is sufficiently informative and if the content of the abstract is consistent with the rest of the paper. The NAR study indicated that 40% of respondents could determine whether an article would be of interest to them based on the abstract alone 60-80% of the time, while 32% could judge an article based on the abstract 80-100% of the time ( 14 ). This demonstrates that the abstract alone is often used to assess the value of an article.

The introduction of a scientific paper presents the research question in the context of what is already known about the topic, in order to identify why the question being studied is of interest to the scientific community, and what gap in knowledge the study aims to fill ( 15 ). The introduction identifies the study’s purpose and scope, briefly describes the general methods of investigation, and outlines the hypothesis and predictions ( 15 ). The peer reviewer determines whether the introduction provides sufficient background information on the research topic, and ensures that the research question and hypothesis are clearly identifiable.

The methods section describes the experimental procedures, and explains why each experiment was conducted. The methods section also includes the equipment and reagents used in the investigation. The methods section should be detailed enough that it can be used it to repeat the experiment ( 15 ). Methods are written in the past tense and in the active voice. The peer reviewer assesses whether the appropriate methods were used to answer the research question, and if they were written with sufficient detail. If information is missing from the methods section, it is the peer reviewer’s job to identify what details need to be added.

The results section is where the outcomes of the experiment and trends in the data are explained without judgement, bias or interpretation ( 15 ). This section can include statistical tests performed on the data, as well as figures and tables in addition to the text. The peer reviewer ensures that the results are described with sufficient detail, and determines their credibility. Reviewers also confirm that the text is consistent with the information presented in tables and figures, and that all figures and tables included are important and relevant ( 15 ). The peer reviewer will also make sure that table and figure captions are appropriate both contextually and in length, and that tables and figures present the data accurately.

The discussion section is where the data is analyzed. Here, the results are interpreted and related to past studies ( 15 ). The discussion describes the meaning and significance of the results in terms of the research question and hypothesis, and states whether the hypothesis was supported or rejected. This section may also provide possible explanations for unusual results and suggestions for future research ( 15 ). The discussion should end with a conclusions section that summarizes the major findings of the investigation. The peer reviewer determines whether the discussion is clear and focused, and whether the conclusions are an appropriate interpretation of the results. Reviewers also ensure that the discussion addresses the limitations of the study, any anomalies in the results, the relationship of the study to previous research, and the theoretical implications and practical applications of the study.

The references are found at the end of the paper, and list all of the information sources cited in the text to describe the background, methods, and/or interpret results. Depending on the citation method used, the references are listed in alphabetical order according to author last name, or numbered according to the order in which they appear in the paper. The peer reviewer ensures that references are used appropriately, cited accurately, formatted correctly, and that none are missing.

Finally, the peer reviewer determines whether the paper is clearly written and if the content seems logical. After thoroughly reading through the entire manuscript, they determine whether it meets the journal’s standards for publication,

and whether it falls within the top 25% of papers in its field ( 16 ) to determine priority for publication. An overview of what a peer reviewer looks for when evaluating a manuscript, in order of importance, is presented in Figure 2 .

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How a peer review evaluates a manuscript

To increase the chance of success in the peer review process, the author must ensure that the paper fully complies with the journal guidelines before submission. The author must also be open to criticism and suggested revisions, and learn from mistakes made in previous submissions.

ADVANTAGES AND DISADVANTAGES OF THE DIFFERENT TYPES OF PEER REVIEW

The peer review process is generally conducted in one of three ways: open review, single-blind review, or double-blind review. In an open review, both the author of the paper and the peer reviewer know one another’s identity. Alternatively, in single-blind review, the reviewer’s identity is kept private, but the author’s identity is revealed to the reviewer. In double-blind review, the identities of both the reviewer and author are kept anonymous. Open peer review is advantageous in that it prevents the reviewer from leaving malicious comments, being careless, or procrastinating completion of the review ( 2 ). It encourages reviewers to be open and honest without being disrespectful. Open reviewing also discourages plagiarism amongst authors ( 2 ). On the other hand, open peer review can also prevent reviewers from being honest for fear of developing bad rapport with the author. The reviewer may withhold or tone down their criticisms in order to be polite ( 2 ). This is especially true when younger reviewers are given a more esteemed author’s work, in which case the reviewer may be hesitant to provide criticism for fear that it will damper their relationship with a superior ( 2 ). According to the Sense About Science survey, editors find that completely open reviewing decreases the number of people willing to participate, and leads to reviews of little value ( 12 ). In the aforementioned study by the PRC, only 23% of authors surveyed had experience with open peer review ( 7 ).

Single-blind peer review is by far the most common. In the PRC study, 85% of authors surveyed had experience with single-blind peer review ( 7 ). This method is advantageous as the reviewer is more likely to provide honest feedback when their identity is concealed ( 2 ). This allows the reviewer to make independent decisions without the influence of the author ( 2 ). The main disadvantage of reviewer anonymity, however, is that reviewers who receive manuscripts on subjects similar to their own research may be tempted to delay completing the review in order to publish their own data first ( 2 ).

Double-blind peer review is advantageous as it prevents the reviewer from being biased against the author based on their country of origin or previous work ( 2 ). This allows the paper to be judged based on the quality of the content, rather than the reputation of the author. The Sense About Science survey indicates that 76% of researchers think double-blind peer review is a good idea ( 12 ), and the PRC survey indicates that 45% of authors have had experience with double-blind peer review ( 7 ). The disadvantage of double-blind peer review is that, especially in niche areas of research, it can sometimes be easy for the reviewer to determine the identity of the author based on writing style, subject matter or self-citation, and thus, impart bias ( 2 ).

Masking the author’s identity from peer reviewers, as is the case in double-blind review, is generally thought to minimize bias and maintain review quality. A study by Justice et al. in 1998 investigated whether masking author identity affected the quality of the review ( 17 ). One hundred and eighteen manuscripts were randomized; 26 were peer reviewed as normal, and 92 were moved into the ‘intervention’ arm, where editor quality assessments were completed for 77 manuscripts and author quality assessments were completed for 40 manuscripts ( 17 ). There was no perceived difference in quality between the masked and unmasked reviews. Additionally, the masking itself was often unsuccessful, especially with well-known authors ( 17 ). However, a previous study conducted by McNutt et al. had different results ( 18 ). In this case, blinding was successful 73% of the time, and they found that when author identity was masked, the quality of review was slightly higher ( 18 ). Although Justice et al. argued that this difference was too small to be consequential, their study targeted only biomedical journals, and the results cannot be generalized to journals of a different subject matter ( 17 ). Additionally, there were problems masking the identities of well-known authors, introducing a flaw in the methods. Regardless, Justice et al. concluded that masking author identity from reviewers may not improve review quality ( 17 ).

In addition to open, single-blind and double-blind peer review, there are two experimental forms of peer review. In some cases, following publication, papers may be subjected to post-publication peer review. As many papers are now published online, the scientific community has the opportunity to comment on these papers, engage in online discussions and post a formal review. For example, online publishers PLOS and BioMed Central have enabled scientists to post comments on published papers if they are registered users of the site ( 10 ). Philica is another journal launched with this experimental form of peer review. Only 8% of authors surveyed in the PRC study had experience with post-publication review ( 7 ). Another experimental form of peer review called Dynamic Peer Review has also emerged. Dynamic peer review is conducted on websites such as Naboj, which allow scientists to conduct peer reviews on articles in the preprint media ( 19 ). The peer review is conducted on repositories and is a continuous process, which allows the public to see both the article and the reviews as the article is being developed ( 19 ). Dynamic peer review helps prevent plagiarism as the scientific community will already be familiar with the work before the peer reviewed version appears in print ( 19 ). Dynamic review also reduces the time lag between manuscript submission and publishing. An example of a preprint server is the ‘arXiv’ developed by Paul Ginsparg in 1991, which is used primarily by physicists ( 19 ). These alternative forms of peer review are still un-established and experimental. Traditional peer review is time-tested and still highly utilized. All methods of peer review have their advantages and deficiencies, and all are prone to error.

PEER REVIEW OF OPEN ACCESS JOURNALS

Open access (OA) journals are becoming increasingly popular as they allow the potential for widespread distribution of publications in a timely manner ( 20 ). Nevertheless, there can be issues regarding the peer review process of open access journals. In a study published in Science in 2013, John Bohannon submitted 304 slightly different versions of a fictional scientific paper (written by a fake author, working out of a non-existent institution) to a selected group of OA journals. This study was performed in order to determine whether papers submitted to OA journals are properly reviewed before publication in comparison to subscription-based journals. The journals in this study were selected from the Directory of Open Access Journals (DOAJ) and Biall’s List, a list of journals which are potentially predatory, and all required a fee for publishing ( 21 ). Of the 304 journals, 157 accepted a fake paper, suggesting that acceptance was based on financial interest rather than the quality of article itself, while 98 journals promptly rejected the fakes ( 21 ). Although this study highlights useful information on the problems associated with lower quality publishers that do not have an effective peer review system in place, the article also generalizes the study results to all OA journals, which can be detrimental to the general perception of OA journals. There were two limitations of the study that made it impossible to accurately determine the relationship between peer review and OA journals: 1) there was no control group (subscription-based journals), and 2) the fake papers were sent to a non-randomized selection of journals, resulting in bias.

JOURNAL ACCEPTANCE RATES

Based on a recent survey, the average acceptance rate for papers submitted to scientific journals is about 50% ( 7 ). Twenty percent of the submitted manuscripts that are not accepted are rejected prior to review, and 30% are rejected following review ( 7 ). Of the 50% accepted, 41% are accepted with the condition of revision, while only 9% are accepted without the request for revision ( 7 ).

SATISFACTION WITH THE PEER REVIEW SYSTEM

Based on a recent survey by the PRC, 64% of academics are satisfied with the current system of peer review, and only 12% claimed to be ‘dissatisfied’ ( 7 ). The large majority, 85%, agreed with the statement that ‘scientific communication is greatly helped by peer review’ ( 7 ). There was a similarly high level of support (83%) for the idea that peer review ‘provides control in scientific communication’ ( 7 ).

HOW TO PEER REVIEW EFFECTIVELY

The following are ten tips on how to be an effective peer reviewer as indicated by Brian Lucey, an expert on the subject ( 22 ):

1) Be professional

Peer review is a mutual responsibility among fellow scientists, and scientists are expected, as part of the academic community, to take part in peer review. If one is to expect others to review their work, they should commit to reviewing the work of others as well, and put effort into it.

2) Be pleasant

If the paper is of low quality, suggest that it be rejected, but do not leave ad hominem comments. There is no benefit to being ruthless.

3) Read the invite

When emailing a scientist to ask them to conduct a peer review, the majority of journals will provide a link to either accept or reject. Do not respond to the email, respond to the link.

4) Be helpful

Suggest how the authors can overcome the shortcomings in their paper. A review should guide the author on what is good and what needs work from the reviewer’s perspective.

5) Be scientific

The peer reviewer plays the role of a scientific peer, not an editor for proofreading or decision-making. Don’t fill a review with comments on editorial and typographic issues. Instead, focus on adding value with scientific knowledge and commenting on the credibility of the research conducted and conclusions drawn. If the paper has a lot of typographical errors, suggest that it be professionally proof edited as part of the review.

6) Be timely

Stick to the timeline given when conducting a peer review. Editors track who is reviewing what and when and will know if someone is late on completing a review. It is important to be timely both out of respect for the journal and the author, as well as to not develop a reputation of being late for review deadlines.

7) Be realistic

The peer reviewer must be realistic about the work presented, the changes they suggest and their role. Peer reviewers may set the bar too high for the paper they are editing by proposing changes that are too ambitious and editors must override them.

8) Be empathetic

Ensure that the review is scientific, helpful and courteous. Be sensitive and respectful with word choice and tone in a review.

Remember that both specialists and generalists can provide valuable insight when peer reviewing. Editors will try to get both specialised and general reviewers for any particular paper to allow for different perspectives. If someone is asked to review, the editor has determined they have a valid and useful role to play, even if the paper is not in their area of expertise.

10) Be organised

A review requires structure and logical flow. A reviewer should proofread their review before submitting it for structural, grammatical and spelling errors as well as for clarity. Most publishers provide short guides on structuring a peer review on their website. Begin with an overview of the proposed improvements; then provide feedback on the paper structure, the quality of data sources and methods of investigation used, the logical flow of argument, and the validity of conclusions drawn. Then provide feedback on style, voice and lexical concerns, with suggestions on how to improve.

In addition, the American Physiology Society (APS) recommends in its Peer Review 101 Handout that peer reviewers should put themselves in both the editor’s and author’s shoes to ensure that they provide what both the editor and the author need and expect ( 11 ). To please the editor, the reviewer should ensure that the peer review is completed on time, and that it provides clear explanations to back up recommendations. To be helpful to the author, the reviewer must ensure that their feedback is constructive. It is suggested that the reviewer take time to think about the paper; they should read it once, wait at least a day, and then re-read it before writing the review ( 11 ). The APS also suggests that Graduate students and researchers pay attention to how peer reviewers edit their work, as well as to what edits they find helpful, in order to learn how to peer review effectively ( 11 ). Additionally, it is suggested that Graduate students practice reviewing by editing their peers’ papers and asking a faculty member for feedback on their efforts. It is recommended that young scientists offer to peer review as often as possible in order to become skilled at the process ( 11 ). The majority of students, fellows and trainees do not get formal training in peer review, but rather learn by observing their mentors. According to the APS, one acquires experience through networking and referrals, and should therefore try to strengthen relationships with journal editors by offering to review manuscripts ( 11 ). The APS also suggests that experienced reviewers provide constructive feedback to students and junior colleagues on their peer review efforts, and encourages them to peer review to demonstrate the importance of this process in improving science ( 11 ).

The peer reviewer should only comment on areas of the manuscript that they are knowledgeable about ( 23 ). If there is any section of the manuscript they feel they are not qualified to review, they should mention this in their comments and not provide further feedback on that section. The peer reviewer is not permitted to share any part of the manuscript with a colleague (even if they may be more knowledgeable in the subject matter) without first obtaining permission from the editor ( 23 ). If a peer reviewer comes across something they are unsure of in the paper, they can consult the literature to try and gain insight. It is important for scientists to remember that if a paper can be improved by the expertise of one of their colleagues, the journal must be informed of the colleague’s help, and approval must be obtained for their colleague to read the protected document. Additionally, the colleague must be identified in the confidential comments to the editor, in order to ensure that he/she is appropriately credited for any contributions ( 23 ). It is the job of the reviewer to make sure that the colleague assisting is aware of the confidentiality of the peer review process ( 23 ). Once the review is complete, the manuscript must be destroyed and cannot be saved electronically by the reviewers ( 23 ).

COMMON ERRORS IN SCIENTIFIC PAPERS

When performing a peer review, there are some common scientific errors to look out for. Most of these errors are violations of logic and common sense: these may include contradicting statements, unwarranted conclusions, suggestion of causation when there is only support for correlation, inappropriate extrapolation, circular reasoning, or pursuit of a trivial question ( 24 ). It is also common for authors to suggest that two variables are different because the effects of one variable are statistically significant while the effects of the other variable are not, rather than directly comparing the two variables ( 24 ). Authors sometimes oversee a confounding variable and do not control for it, or forget to include important details on how their experiments were controlled or the physical state of the organisms studied ( 24 ). Another common fault is the author’s failure to define terms or use words with precision, as these practices can mislead readers ( 24 ). Jargon and/or misused terms can be a serious problem in papers. Inaccurate statements about specific citations are also a common occurrence ( 24 ). Additionally, many studies produce knowledge that can be applied to areas of science outside the scope of the original study, therefore it is better for reviewers to look at the novelty of the idea, conclusions, data, and methodology, rather than scrutinize whether or not the paper answered the specific question at hand ( 24 ). Although it is important to recognize these points, when performing a review it is generally better practice for the peer reviewer to not focus on a checklist of things that could be wrong, but rather carefully identify the problems specific to each paper and continuously ask themselves if anything is missing ( 24 ). An extremely detailed description of how to conduct peer review effectively is presented in the paper How I Review an Original Scientific Article written by Frederic G. Hoppin, Jr. It can be accessed through the American Physiological Society website under the Peer Review Resources section.

CRITICISM OF PEER REVIEW

A major criticism of peer review is that there is little evidence that the process actually works, that it is actually an effective screen for good quality scientific work, and that it actually improves the quality of scientific literature. As a 2002 study published in the Journal of the American Medical Association concluded, ‘Editorial peer review, although widely used, is largely untested and its effects are uncertain’ ( 25 ). Critics also argue that peer review is not effective at detecting errors. Highlighting this point, an experiment by Godlee et al. published in the British Medical Journal (BMJ) inserted eight deliberate errors into a paper that was nearly ready for publication, and then sent the paper to 420 potential reviewers ( 7 ). Of the 420 reviewers that received the paper, 221 (53%) responded, the average number of errors spotted by reviewers was two, no reviewer spotted more than five errors, and 35 reviewers (16%) did not spot any.

Another criticism of peer review is that the process is not conducted thoroughly by scientific conferences with the goal of obtaining large numbers of submitted papers. Such conferences often accept any paper sent in, regardless of its credibility or the prevalence of errors, because the more papers they accept, the more money they can make from author registration fees ( 26 ). This misconduct was exposed in 2014 by three MIT graduate students by the names of Jeremy Stribling, Dan Aguayo and Maxwell Krohn, who developed a simple computer program called SCIgen that generates nonsense papers and presents them as scientific papers ( 26 ). Subsequently, a nonsense SCIgen paper submitted to a conference was promptly accepted. Nature recently reported that French researcher Cyril Labbé discovered that sixteen SCIgen nonsense papers had been used by the German academic publisher Springer ( 26 ). Over 100 nonsense papers generated by SCIgen were published by the US Institute of Electrical and Electronic Engineers (IEEE) ( 26 ). Both organisations have been working to remove the papers. Labbé developed a program to detect SCIgen papers and has made it freely available to ensure publishers and conference organizers do not accept nonsense work in the future. It is available at this link: http://scigendetect.on.imag.fr/main.php ( 26 ).

Additionally, peer review is often criticized for being unable to accurately detect plagiarism. However, many believe that detecting plagiarism cannot practically be included as a component of peer review. As explained by Alice Tuff, development manager at Sense About Science, ‘The vast majority of authors and reviewers think peer review should detect plagiarism (81%) but only a minority (38%) think it is capable. The academic time involved in detecting plagiarism through peer review would cause the system to grind to a halt’ ( 27 ). Publishing house Elsevier began developing electronic plagiarism tools with the help of journal editors in 2009 to help improve this issue ( 27 ).

It has also been argued that peer review has lowered research quality by limiting creativity amongst researchers. Proponents of this view claim that peer review has repressed scientists from pursuing innovative research ideas and bold research questions that have the potential to make major advances and paradigm shifts in the field, as they believe that this work will likely be rejected by their peers upon review ( 28 ). Indeed, in some cases peer review may result in rejection of innovative research, as some studies may not seem particularly strong initially, yet may be capable of yielding very interesting and useful developments when examined under different circumstances, or in the light of new information ( 28 ). Scientists that do not believe in peer review argue that the process stifles the development of ingenious ideas, and thus the release of fresh knowledge and new developments into the scientific community.

Another issue that peer review is criticized for, is that there are a limited number of people that are competent to conduct peer review compared to the vast number of papers that need reviewing. An enormous number of papers published (1.3 million papers in 23,750 journals in 2006), but the number of competent peer reviewers available could not have reviewed them all ( 29 ). Thus, people who lack the required expertise to analyze the quality of a research paper are conducting reviews, and weak papers are being accepted as a result. It is now possible to publish any paper in an obscure journal that claims to be peer-reviewed, though the paper or journal itself could be substandard ( 29 ). On a similar note, the US National Library of Medicine indexes 39 journals that specialize in alternative medicine, and though they all identify themselves as “peer-reviewed”, they rarely publish any high quality research ( 29 ). This highlights the fact that peer review of more controversial or specialized work is typically performed by people who are interested and hold similar views or opinions as the author, which can cause bias in their review. For instance, a paper on homeopathy is likely to be reviewed by fellow practicing homeopaths, and thus is likely to be accepted as credible, though other scientists may find the paper to be nonsense ( 29 ). In some cases, papers are initially published, but their credibility is challenged at a later date and they are subsequently retracted. Retraction Watch is a website dedicated to revealing papers that have been retracted after publishing, potentially due to improper peer review ( 30 ).

Additionally, despite its many positive outcomes, peer review is also criticized for being a delay to the dissemination of new knowledge into the scientific community, and as an unpaid-activity that takes scientists’ time away from activities that they would otherwise prioritize, such as research and teaching, for which they are paid ( 31 ). As described by Eva Amsen, Outreach Director for F1000Research, peer review was originally developed as a means of helping editors choose which papers to publish when journals had to limit the number of papers they could print in one issue ( 32 ). However, nowadays most journals are available online, either exclusively or in addition to print, and many journals have very limited printing runs ( 32 ). Since there are no longer page limits to journals, any good work can and should be published. Consequently, being selective for the purpose of saving space in a journal is no longer a valid excuse that peer reviewers can use to reject a paper ( 32 ). However, some reviewers have used this excuse when they have personal ulterior motives, such as getting their own research published first.

RECENT INITIATIVES TOWARDS IMPROVING PEER REVIEW

F1000Research was launched in January 2013 by Faculty of 1000 as an open access journal that immediately publishes papers (after an initial check to ensure that the paper is in fact produced by a scientist and has not been plagiarised), and then conducts transparent post-publication peer review ( 32 ). F1000Research aims to prevent delays in new science reaching the academic community that are caused by prolonged publication times ( 32 ). It also aims to make peer reviewing more fair by eliminating any anonymity, which prevents reviewers from delaying the completion of a review so they can publish their own similar work first ( 32 ). F1000Research offers completely open peer review, where everything is published, including the name of the reviewers, their review reports, and the editorial decision letters ( 32 ).

PeerJ was founded by Jason Hoyt and Peter Binfield in June 2012 as an open access, peer reviewed scholarly journal for the Biological and Medical Sciences ( 33 ). PeerJ selects articles to publish based only on scientific and methodological soundness, not on subjective determinants of ‘impact ’, ‘novelty’ or ‘interest’ ( 34 ). It works on a “lifetime publishing plan” model which charges scientists for publishing plans that give them lifetime rights to publish with PeerJ, rather than charging them per publication ( 34 ). PeerJ also encourages open peer review, and authors are given the option to post the full peer review history of their submission with their published article ( 34 ). PeerJ also offers a pre-print review service called PeerJ Pre-prints, in which paper drafts are reviewed before being sent to PeerJ to publish ( 34 ).

Rubriq is an independent peer review service designed by Shashi Mudunuri and Keith Collier to improve the peer review system ( 35 ). Rubriq is intended to decrease redundancy in the peer review process so that the time lost in redundant reviewing can be put back into research ( 35 ). According to Keith Collier, over 15 million hours are lost each year to redundant peer review, as papers get rejected from one journal and are subsequently submitted to a less prestigious journal where they are reviewed again ( 35 ). Authors often have to submit their manuscript to multiple journals, and are often rejected multiple times before they find the right match. This process could take months or even years ( 35 ). Rubriq makes peer review portable in order to help authors choose the journal that is best suited for their manuscript from the beginning, thus reducing the time before their paper is published ( 35 ). Rubriq operates under an author-pay model, in which the author pays a fee and their manuscript undergoes double-blind peer review by three expert academic reviewers using a standardized scorecard ( 35 ). The majority of the author’s fee goes towards a reviewer honorarium ( 35 ). The papers are also screened for plagiarism using iThenticate ( 35 ). Once the manuscript has been reviewed by the three experts, the most appropriate journal for submission is determined based on the topic and quality of the paper ( 35 ). The paper is returned to the author in 1-2 weeks with the Rubriq Report ( 35 ). The author can then submit their paper to the suggested journal with the Rubriq Report attached. The Rubriq Report will give the journal editors a much stronger incentive to consider the paper as it shows that three experts have recommended the paper to them ( 35 ). Rubriq also has its benefits for reviewers; the Rubriq scorecard gives structure to the peer review process, and thus makes it consistent and efficient, which decreases time and stress for the reviewer. Reviewers also receive feedback on their reviews and most significantly, they are compensated for their time ( 35 ). Journals also benefit, as they receive pre-screened papers, reducing the number of papers sent to their own reviewers, which often end up rejected ( 35 ). This can reduce reviewer fatigue, and allow only higher-quality articles to be sent to their peer reviewers ( 35 ).

According to Eva Amsen, peer review and scientific publishing are moving in a new direction, in which all papers will be posted online, and a post-publication peer review will take place that is independent of specific journal criteria and solely focused on improving paper quality ( 32 ). Journals will then choose papers that they find relevant based on the peer reviews and publish those papers as a collection ( 32 ). In this process, peer review and individual journals are uncoupled ( 32 ). In Keith Collier’s opinion, post-publication peer review is likely to become more prevalent as a complement to pre-publication peer review, but not as a replacement ( 35 ). Post-publication peer review will not serve to identify errors and fraud but will provide an additional measurement of impact ( 35 ). Collier also believes that as journals and publishers consolidate into larger systems, there will be stronger potential for “cascading” and shared peer review ( 35 ).

CONCLUDING REMARKS

Peer review has become fundamental in assisting editors in selecting credible, high quality, novel and interesting research papers to publish in scientific journals and to ensure the correction of any errors or issues present in submitted papers. Though the peer review process still has some flaws and deficiencies, a more suitable screening method for scientific papers has not yet been proposed or developed. Researchers have begun and must continue to look for means of addressing the current issues with peer review to ensure that it is a full-proof system that ensures only quality research papers are released into the scientific community.

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A scientific essay is common writing among science students or anyone undertaking a science-related course.

Writing a well-curated and clear science essayservice is necessary if you’re aspiring to get good grades. This can only be achieved if one has a concise knowledge of how to write a good essay that contains all the necessary facts, details, and subject, although there are online essay writing services that can help you ace out the writing process with the help of their expert writers.

What is a scientific essay?

A scientific essay is an article, essay, or journal written to ascertain a particular problem, whereby you have analyzed and proffered a possible solution to the stated problem based on an experiment carried out by you or by utilizing available theories and experiments. This form of writing may involve reporting scientific observations, theories, and hypotheses in a manner that even a non-scientist can understand.

Characteristic of a scientific essay:

1.Well conventional and structured format: this simply explains the need to follow the scientific writing structural pattern, which includes:

Aim : This highlights the main purpose and reason why an experiment was carried out.
Abstract : This is a short and concise summary of everything contained in the report/writing.
Method : This involves the description of all the activities, the processes, and all events that were carried out to achieve the total end result.
Result : This is a clear explanation of all observations and interpretations of the project.
Discussion : This section discusses and critically analyzes, evaluates, and discusses your result’s significance. Also, it compares previous studies, discusses and also suggests solutions to weaknesses.
References : This depends on the type of scientific writing you’re engaging in. It follows a reference format, the citation is a must, and Harvard style is widely used in most scientific writing.

2. Contains a figure, charts, and images: A scientific essay contains a record of all data taken from the experiment, these can be illustrated in the writing with tables, charts, images, graphs e.t.c. Each illustration gives a quick description of the detailed report.

3.Comprehensive and conveys the idea discussed: prior to a different form of the report and essay writing, one thing that sets out a scientific essay is the complexity and compact writing is its ability to convey sequentially a particular idea. Each sentence focuses on the subject and the concept of the discussion.

4.Language use in scientific writing is different: Unlike other types of essay writing where slang and emotional phrases can be incorporated, scientific writing uses scientific terms and wordings. Examples include; use of “offsprings” instead of “babies” in genetic terms.

5.Conclusion: A good scientific writing contains a conclusion page. This page contains a validation or disagreement, interpretation, and outcome of the research. A good scientific essay interprets results and also states whether the report agrees or disagrees with existing work or the topic of other authors in the field.

Qualities of a good scientific essay

Unlike the other type of essay writings, scientific essays possess special qualities that make them more unique and different from other forms of essays, which include;

It is clear and concise
Use formal languages rather than informal
Avoids use of direct quotes
Uses up-to-date illustrations, data, and findings.
Arrives at a conclusion.

With the above-mentioned qualities of a good scientific essay, you might be interested in learning how to write a scientific essay, here is a guideline.

How to successfully write a good scientific essay

Topic selection.

Most universities give out topics of discussion to students or ask them to select a topic of choice and discuss.

Topic selection is the foundation of any scientific writing. It serves as a guide to what type of information you will be providing, what type of information you will be gathering, thereby allowing you to narrow your search.

When selecting a topic, you shouldn’t select a complex task. Selecting a complex task or topic, makes the whole process of writing, crafting, and research boring and time-consuming.

Draft your work plan : Drafting a work plan will help save you from unorganized writing. Create an outline, an outline acts as a road map for everything you plan on including in the essay.
Start : After concluding on your topic, drafting, the next step is to start writing. With an already established outline, writing your essay will be easier. Make sure to write in a formal tone, arrange your essay in such a way it follows the standard scientific essay writing guideline. Also, conclude your scientific essay by summing up all the points you have earlier highlighted in your essay body.
Conclude your essay : This is the final part of your scientific essay. This section summarizes the whole content of the essay, it includes all theories, relevant and irrelevant hypotheses, and implications of the result.
Proofread : This is also an important aspect of writing, it is the act of carefully checking out errors and mistakes in an essay before it is finally published. Proofreading allows you to identify errors you have probably overlooked in first writing. This is because submitting an essay filled with errors can affect your grade and overall performance, you can employ the help of a friend or Check out Ca.CustomWritings.com , they offer professional essay writing services.

With all carefully highlighted above, we have explained ways on how to successfully write a scientific essay. Writing a scientific essay involves you getting your facts, figures, and data right.

Also, it involves understanding the subject of which you are trying to address. A scientific essay is far different from any other form of writing, and formatting it the right way is the best option.

Thinking of giving the task out to a writing agency? Ca.CustomWritings.com is your best option to try out. They have over a thousand professionals, with reliable customer service.

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The correct way to communicate your degree to employers and others is by using the following formats:

Degree - This is the academic degree you are receiving. Your major is in addition to the degree; it can be added to the phrase or written separately. Include the full name of your degree, major(s), minor(s), emphases, and certificates on your resume.

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Example: Primary Major: Psychology ; Secondary Major: Marketing

Bachelor of Arts Degree in Psychology & Marketing

Primary Major: Marketing ; Secondary Major: Psychology

Bachelor of Science Degree in Marketing & Psychology

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In May 20XX, I will graduate with my Bachelor's degree in International Affairs.
In December 20XX, I will graduate with my Master's degree in Counseling Education.

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What is scientific writing?
Scientific writing is a technical form of writing that is designed to communicate scientific information to other scientists. Depending on the specific scientific genre—a journal article, a scientific poster, or a research proposal, for example—some aspects of the writing may change, such as its purpose, audience, or organization.Many aspects of scientific writing, however, vary little ...
Scientific Paper: What is it & How to Write it? (Steps and Format)
Scientific papers are the medium through which scientists report their work to the world. Their professional reputation is based on how these papers are acknowledged by the scientific community. No matter how great the actual experiment is, a poorly written scientific paper may negatively affect one's professional honor, or worse, prevent the ...
How to successfully write a scientific essay
Conclude your essay by summarizing all the key points. Also, highlight the practical potential of our findings and their impacts. Proofread and check for errors in the paper. Before submitting or forwarding your article, it is fundamental that you proofread and correct all the errors that you come across.
Scientific Writing Made Easy: A Step‐by‐Step Guide to Undergraduate
Regardless of the specific course being taught, this guide can be used as a reference when writing scientific papers, independent research projects, and laboratory reports. For students looking for more in-depth advice, additional resources are listed at the end of the guide. ... Define the hypotheses you wish to address, state the approach of ...
How to Write a Scientific Essay
Take concise notes while reading, focusing on information relevant to the essay. Identify the most crucial information and examples that support the argument. Begin writing the essay, considering starting with the middle sections for clarity. Circle back to the introduction and conclusion once the main body is outlined.
PDF Tutorial Essays for Science Subjects
read articles about science in newspapers and magazines, as well as popular science books. It's important that you realize that there is a distinction between writing for non-specialists and the style that you will need for your essays. In explaining scientific discoveries, popular science writers and journalists want to:
PDF WRITING A SCIENTIFIC ESSAY
Define. the problem or research area . 2. Present the background context. of the work . 3. Introduce/ o. utline of how your research fits into the theoretical framework. established around the area . 4. State . your viewpoint or argument . 1. Explain. different perspectives of the problem . 2. Critically Examine. the material read . Either from ...
Definition and Examples of Science Writing
Examples and Observations "Because science writing is intended to be entertaining enough to capture the continued interest of potential readers, its style is much less somber than the usual scientific writing [i.e., definition No. 2, above]. The use of slang, puns, and other word plays on the English language are accepted and even encouraged. . . . ...
Scientific Papers
Scientific papers typically have two audiences: first, the referees, who help the journal editor decide whether a paper is suitable for publication; and second, the journal readers themselves, who ...
Guide: Writing the Scientific Paper
The scientific paper has developed over the past three centuries into a tool to communicate the results of scientific inquiry. The main audience for scientific papers is extremely specialized. The purpose of these papers is twofold: to present information so that it is easy to retrieve, and to present enough information that the reader can ...
The Science Essay
The science essay uses science to think about the human condition; it uses humanistic thinking to reflect on the possibilities and limits of science and technology. In this class we read and practice writing science essays of varied lengths and purposes. We will read a wide variety of science essays, ranging across disciplines, both to learn more about this genre and to inspire your own writing.
How to Write a Scientific Essay • Oxford Learning College
Essays need to be written out in continuous prose. You shouldn't be using bullet points or writing in note form. If it helps to make a particular point, however, you can use a diagram providing it is relevant and adequately explained. Look at the topic you are required to write about.
How to Write a Scientific Essay to Meet Academic Standards
The scientific essay meaning is crucial as it explains complex events, things or terms from the scientific viewpoint. It's not a simple essay about how you feel today. That is a very important, durable and complex labor. Therefore, this assignment cannot be referred to as the easiest research projects. Nonetheless, it is undoubtedly one of ...
Scientific writing
Scientific writing is writing about science, with an implication that the writing is by scientists and for an audience that primarily includes peers—those with sufficient expertise to follow in detail. ( The similar term "science writing" instead tends to refer to writing about a scientific topic for a general audience; this could be by scientists and/or journalists, for example.)
Scientific Essay
Parts of a scientific essay. A scientific essay consists of the following elements: Title . It is the name that the scientific essay will bear. It is important that it is original and refers to the content of the writing. Introduction . The topic that the essay will address is raised and the hypotheses or what explains the reason for the choice ...
Scientific Essay Format: Definition and Features
A scientific essay is an article or journal that addresses a specific problem. It follows the standards of academic essay writing. The essay must include the main structure - introduction, body, and conclusion. The student captures more details, such as an abstract, methodology, and results.
Scientific literature
Scientific literature comprises academic papers that report original empirical and theoretical work in the natural and social sciences.Within a field of research, relevant papers are often referred to as "the literature".Academic publishing is the process of contributing the results of one's research into the literature, which often requires a peer-review process.
Scientific Discovery
Scientific discovery is the process or product of successful scientific inquiry. Objects of discovery can be things, events, processes, causes, and properties as well as theories and hypotheses and their features (their explanatory power, for example). Most philosophical discussions of scientific discoveries focus on the generation of new ...
Scientific Progress
Scientific Progress. Science is often distinguished from other domains of human culture by its progressive nature: in contrast to art, religion, philosophy, morality, and politics, there exist clear standards or normative criteria for identifying improvements and advances in science. For example, the historian of science George Sarton argued ...
Peer Review in Scientific Publications: Benefits, Critiques, & A
Scientific papers submitted for peer review usually follow a specific structure that begins with the title, followed by the abstract, introduction, methodology, results, discussion, conclusions, and references. ... Another common fault is the author's failure to define terms or use words with precision, as these practices can mislead readers ...
Essay on Science: Meaning, Scope, Nature, Technology and Society
Essay # 1. Meaning and Definitions of Science: Meaning of Science: The English word Science is derived from a Latin Verb 'Scire', which means 'to know' and Latin Noun 'Scientia' which means 'knowledge'. Meaning of Science is based on German word ' Wissenchaft', which means systematic, organized knowledge. Thus, Science is a ...
Scientific Essay Format: Definition and Features
Scientific Essay Format: Definition and Features. A scientific essay is common writing among science students or anyone undertaking a science-related course. Writing a well-curated and clear science essayservice is necessary if you're aspiring to get good grades. This can only be achieved if one has a concise knowledge of how to write a good ...
Properly Write Your Degree
The correct way to communicate your degree to employers and others is by using the following formats: Degree - This is the academic degree you are receiving. Your major is in addition to the degree; it can be added to the phrase or written separately. Include the full name of your degree, major (s), minor (s), emphases, and certificates on your ...
Scientific Essay Meaning
Scientific Essay Meaning, Resume Software Trial, Hiv And Tb Hesi Case Study Quizlet, Polygraph Essay Topics, What Fsu Is Looking For In Their Essay, Dell Business Plan Competition, Ted Talk Essay Writing There are questions about essay writing services that students ask about pretty often. So we've decided to answer them in the form of an F.A.Q.

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Scientific Paper: What is it & How to Write it? (Steps and Format)

What is a Scientific Paper? (Definition)

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Why are Scientific Papers Important?

How to Write a Scientific Paper? (Steps & Format)

Step 1. Add Title in the Paper

Step 2. Mention Keywords List

Step 3. Add Abstract

Step 4. Start with Introduction

Step 5. Mention Scientific Materials and Methods Used

Step 6. Write down Results

Step 7. Create a Discussion Section

Step 8. Mention References

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