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A Political Science Guide

For students, researchers, and others interested in doing the work of political science, formulating/extracting hypotheses.

Formulating hypotheses, which are defined as propositions set forth to explain a group of facts or phenomena, is a fundamental component to any research scholarship. Hypotheses lay out the central arguments that will be tested and either verified or rejected in the body of a paper. Papers may address multiple competing or supporting hypotheses in order to account for the full spectrum of explanations that could account for the phenomenon being studied. As such, hypotheses often include statements about a presumed impact of an independent variable on a dependent variable.

Hypotheses should not emanate from preconceived perceptions about a given relationship between variables, but rather should come about as a product of research. Thus, hypotheses should be formed after developing an understanding of the relevant literature to a given topic rather than before conducting research. Beginning research with a specific argument in mind can lead to discounting other evidence that could either run counter to this preconceived argument or could point to other potential explanations.

There are a number of different types of hypotheses utilized in political science research:

• Null hypothesis: states that there is no relationship between two concepts
• Correlative hypothesis: states that there is a relationship, between two or more concepts or variables, but doesn’t specify the nature of a relationship
• Directional hypothesis: states the nature of the relationship between concepts or variables. These types of relationships can include positive, negative (inverse), high or low levels of influence, etc.
• Causal hypothesis: states that one variable causes the other

A good hypothesis should be both correlative and directional and most hypotheses in political science research will also be causal, asserting the impact of an independent variable on a dependent variable.

There are a number of additional considerations that must be taken into account in order to make a hypothesis as strong as possible:

• Hypotheses  must be falsifiable , that is able to be empirically tested. They cannot attribute causation to something like a supernatural entity whose existence can neither be proven nor denied.
• Hypotheses must be internally consistent , that is that they must be proving what they claim to be proving and must not contain any logical or analytical contradiction
• Hypotheses must have clearly defined outcomes (dependent variables) that are both dependent and vary based on the dependent variable.
• Hypotheses must be general and should aim to explain as much as possible with as little as possible. As such, hypotheses should have as few exceptions as possible and should not rely on amorphous concepts like ‘national interest.’
• Hypotheses must be empirical statements that are propositions about relationships that exist in the real world.
• Hypotheses must be plausible (there must be a logical reason why they might be true) and should be specific (the relationship between variables must be expressed as explicitly as possible) and directional.
• Fearon, James D. 1991. Counterfactuals and Hypothesis Testing in Political Science . World Politics 43 (2): 169-195.

Abstract : “Scholars in comparative politics and international relations routinely evaluate causal hypotheses by referring to counterfactual cases where a hypothesized causal factor is supposed to have been absent. The methodological status and the viability of this very common procedure are unclear and are worth examining. How does the strategy of counterfactual argument relate, if at all, to methods of hypothesis testing based on the comparison of actual cases, such as regression analysis or Mill’s Method of Difference? Are counterfactual thought experiments a viable means of assessing hypotheses about national and international outcomes, or are they methodologically invalid in principle? The paper addresses the first question in some detail and begins discussion of the second. Examples from work on the causes of World War I, the nonoccurrence of World War III, social revolutions, the breakdown of democratic regimes in Latin America, and the origins of fascism and corporatism in Europe illustrate the use, problems and potential of counterfactual argument in small-N-oriented political science research.” – Jstor.org

• King, Gary, Robert Owen Keohane, and Sidney Verba. 1994. Designing social inquiry: scientific inference in qualitative research. Princeton, NJ: Princeton University Press.
• Palazzolo, David and Dave Roberts. 2010. What is a Good Hypothesis? University of Richmond Writing Center.

Contributor: Harrison Polans

updated July 12, 2017 – MN

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University Libraries

Psci 3300: introduction to political research.

• Library Accounts
• Selecting a Topic for Research
• From Topic to Research Question
• From Question to Theories, Hypotheses, and Research Design
• Annotated Bibliographies
• The Literature Review
• Search Strategies for Ann. Bibliographies & Lit. Reviews
• Find PSCI Books for Ann. Bibliographies & Lit. Reviews
• Databases & Electronic Resources for Your Lit. Review
• Methods, Data Analysis, Results, Limitations, and Conclusion
• Finding Data and Statistics for the Data Analysis
• Citing Sources for the Reference Page

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Hypothesis in Political Science

"A generalization predicting that a relationship exists between variables. Many generalizations about politics are a sort of folklore. Others proceed from earlier work carried out by social scientists. Within the social sciences most statements about behaviour relate to large groups of people. Hence, testing any hypothesis in the field of political science will involve statistical method. It will be dealing with probabilities.

To test a hypothesis one must pose a null hypothesis. If we wanted to test the validity of the common generalization, 'manual workers tend to vote for the Labour Party' we would begin by assuming the statement was untrue. The investigation would require a sample survey in which manual workers were identified and questions put to them. It would need to be done in several constituencies in different parts of the country. Having collated the data we would use the evidence to test the null hypothesis, employing statistical techniques to assess the probability of acquiring such data if the null hypothesis were correct. These techniques are known as 'significance tests'. They estimate the probability that the rejection of a null hypothesis is a mistake. If the statistical tests indicates that the odds against it being a mistake are 1000 to one, then this is stated as a '.001 level of significance'.

The fact that the research showed that it was highly likely that manual workers 'tend' to vote for the Labour vote would not satisfy most political scientists. They also want to understand those who did not. Consequently much more work would need to be done to refine the hypothesis and define the tendency with more accuracy. Whatever the case, a hypothesis in the social sciences about a group or socio-demographic category can never tell us about the behaviour of an individual in that group or category."

Hypothesis. (1999). In F. Bealey. The Blackwell Dictionary of Political Science , Oxford, United Kingdom: Blackwell Publishers.

What a Quantitative Research Design?

Quantitative research studies produce results that can be used to describe or note numerical changes in measurable characteristics of a population of interest; generalize to other, similar situations; provide explanations of predictions; and explain causal relationships. The fundamental philosophy underlying quantitative research is known as positivism, which is based on the scientific method of research. Measurement is necessary if the scientific method is to be used. The scientific method involves an empirical or theoretical basis for the investigation of populations and samples. Hypotheses must be formulated, and observable and measurable data must be gathered. Appropriate mathematical procedures must be used for the statistical analyses required for hypothesis testing.

Quantitative methods depend on the design of the study (experimental, quasi-experimental, non-experimental). Study design takes into account all those elements that surround the plan for the investigation, such as research question or problem statement, research objectives, operational definitions, scope of inferences to be made, assumptions and limitations of the study, independent and dependent variables, treatment and controls, instrumentation, systematic data collection actions, statistical analysis, time lines, and reporting procedures. The elements of a research study and experimental, quasi-experimental, and nonexperimental designs are discussed here.

Elements of Quantitative Design

Problem statement.

First, an empirical or theoretical basis for the research problem should be established. This basis may emanate from personal experiences or established theory relevant to the study. From this basis, the researcher may formulate a research question or problem statement.

Operational Definitions

Operational definitions describe the meaning of specific terms used in a study. They specify the procedures or operations to be followed in producing or measuring complex constructs that hold different meanings for different people. For example, intelligence may be defined for research purposes by scores on the Stanford-Binet Intelligence Scale.

Population and Sample

Quantitative methods include the target group (population) to which the researcher wishes to generalize and the group from which data are collected (sample). Early in the planning phase, the researcher should determine the scope of inference for results of the study. The scope of inference pertains to populations of interest, procedures used to select the sample(s), method for assigning subjects to groups, and the type of statistical analysis to be conducted.

Formulation of Hypotheses

Complex questions to compare responses of two or more groups or show relationships between  two or more variables are best answered by hypothesis testing. A hypothesis is a statement of the researcher's expectations about a relationship between variables.

Hypothesis Testing

Statements of hypotheses may be written in the alternative or null form. A directional alternative hypothesis states the researcher's predicted direction of change, difference between two or more sample means, or relationship among variables. An example of a directional alternative hypothesis is as follows:

Third-grade students who use reading comprehension strategies will score higher on the State Achievement Test than their counterparts who do not use reading comprehension strategies.

A nondirectional alternative hypothesis states the researcher's predictions without giving the direction of the difference. For example:

There will be a difference in the scores on the State Achievement Test between third-grade students who use reading comprehension strategies and those who do not.

Stated in the null form, hypotheses can be tested for statistically significant differences between groups on the dependent variable(s) or statistically significant relationships between and among variables. The null hypothesis uses the form of “no difference” or “no relationship.” Following is an example of a null hypothesis:

There will be no difference in the scores on the State Achievement Test between third-grade students who use reading comprehension strategies and those who do not.

It is important that hypotheses to be tested are stated in the null form because the interpretation of the results of inferential statistics is based on probability. Testing the null hypothesis allows researchers to test whether differences in observed scores are real, or due to chance or error; thus, the null hypothesis can be rejected or retained.

Organization and Preparation of Data for Analysis

Survey forms, inventories, tests, and other data collection instruments returned by participants should be screened prior to the analysis. John Tukey suggested that exploratory data analysis be conducted using graphical techniques such as plots and data summaries in order to take a preliminary look at the data. Exploratory analysis provides insight into the underlying structure of the data. The existence of missing cases, outliers, data entry errors, unexpected or interesting patterns in the data, and whether or not assumptions of the planned analysis are met can be checked with exploratory procedures.

Inferential Statistical Tests

Important considerations for the choice of a statistical test for a particular study are (a) type of research questions to be answered or hypotheses to be tested; (b) number of independent and dependent variables; (c) number of covariates; (d) scale of the measurement instrument(s) (nominal, ordinal, interval, ratio); and (e) type of distribution (normal or non-normal). Examples of statistical procedures commonly used in educational research are  t  test for independent samples, analysis of variance, analysis of covariance, multivariate procedures, Pearson product-moment correlation, Mann–Whitney  U  test, Kruskal–Wallis test, and Friedman's chi-square test.

Results and Conclusions

The level of statistical significance that the researcher sets for a study is closely related to hypothesis testing. This is called the alpha level. It is the level of probability that indicates the maximum risk a researcher is willing to take that observed differences are due to chance. The alpha level may be set at .01, meaning that 1 out of 100 times the results will be due to chance; more commonly, the alpha level is set at .05, meaning that 5 out of 100 times observed results will be due to chance. Alpha levels are often depicted on the normal curve as the critical region, and the researcher must reject the null hypothesis if the data fall into the predetermined critical region. When this occurs, the researcher must conclude that the findings are statistically significant. If the  researcher rejects a true null hypothesis (there is, in fact, no difference between the means), a Type I error has occurred. Essentially, the researcher is saying there is a difference when there is none. On the other hand, if a researcher fails to reject a false null (there is, in fact, a difference), a Type II error has occurred. In this case, the researcher is saying there is no difference when a difference exists. The power in hypothesis testing is the probability of correctly rejecting a false null hypothesis. The cost of committing a Type I or Type II error rests with the consequences of the decisions made as a result of the test. Tests of statistical significance provide information on whether to reject or fail to reject the null hypothesis; however, an effect size ( R 2 , eta 2 , phi, or Cohen's  d ) should be calculated to identify the strength of the conclusions about differences in means or relationships among variables.

Salkind, Neil J. 2010.  Encyclopedia of Research Design . Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412961288 .

Some Terms in Statistics that You Should Know

Bivariate Regression

Central Tendacy, Measures of

Chi-Square Test

Cohen's d Statistic

Cohen's f Statistic

Correspondence Analysis

Cross-Sectional Design

Descriptive Statistics

Effect Size, Measure of

Eta-Squared

Factor Loadings

False Positive

Frequency Tables

Alternative Hypotheses

Null Hypothesis

Krippendorff's Alpha

Multiple Regression

Multivariate Analysis of Variance (MANOVA)

Multivariate Normal Distribution

Partial Eta-Squared

Percentile Rank

Random Error

Reliability 

Regression Discontinuity

Regression to the Mean

Standard Deviation

Significance, Statistical

Trimmed Mean

Variability, Measure of

Is the term you are looking for not here? Review the Encyclopedia of Research Design below. 

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more. Subject coverage includes sociology, health, criminology, education, anthropology, psychology, business, political science, history, economics, among others.

Sage Research Methods has a feature called a Methods Map that can help you explore different types of Research Designs .

You can also explore Cases to see real research using your selected research method to learn how other authors are writing up their findings.

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1.5 Empirical Political Science

Learning outcomes.

By the end of this section, you will be able to:

• Distinguish empirical political science from normative political science.
• Explain what facts are and why they may be disputed.
• Define generalization and discuss when generalizations can be helpful.

Unlike normative political science, empirical political science is based not on what should be, but on what is. It seeks to describe the real world of politics, distinguishing between what is predictable and what is idiosyncratic. Empirical political science attempts to explain and predict. 32

Empirical political science assumes that facts exist: actual, genuine, verifiable facts. Empirical questions are ones that can be answered by factual evidence. The number of votes a candidate receives is an empirical matter: votes can be counted. Counting votes accurately so that each candidate receives the actual number of votes that were cast for them can be difficult. Different ways of counting can lead to slightly different counts, but a correct number actually exists.

Connecting Courses

Empirical political science, as described here, is not different from other applications of the scientific method , whether one is examining rocks in geology, birds in botany, or the human mind in psychology. In every science-based course you take, you will observe systematic efforts to develop knowledge by using data to test hypotheses.

OpenStax Biology, a text generally assigned in introductory college biology courses, begins with a description of science and the scientific method, noting that “one of the most important aspects of this method is the testing of hypotheses . . . by means of repeatable experiments” 33 Until recently, few political science theories could be tested through repeated experiments, so instead political scientists had to rely on repeated observations. Congressional elections in the United States are held every two years, for example, and they generate substantial data that can be used to test hypotheses. In recent years, however, political scientists have conducted more and more true experiments. 34 Political science is connected to biology, and all other courses in science, through the use of the scientific method.

A fact may be disputed. There may be genuine uncertainty as to what the facts really are—what the evidence really shows. Sometimes it is extremely difficult to gather the facts. Do space aliens exist? That is an empirical question. Either space aliens exist, or they do not. Some researchers claim to have evidence that space aliens are real, but their evidence is not universally, or even broadly, accepted. One side of this argument is correct, however, and the other is not. Evidence has not yet conclusively determined which is correct. 35

Does the Russian government seek to interfere with American elections, and if so, does its interference affect the outcome? The first part of the question is difficult (but not impossible) to answer because when a country interferes in another country’s domestic affairs it tries to do so in secret. It is difficult to uncover secrets. 36 But the second part of the question, does the interference affect the outcome, is almost impossible to answer. Because so many factors influence election outcomes, it is extremely challenging to determine which individual factors made any consequential difference. 37

There are thus empirical debates in which people of good faith disagree about what the facts are. In many cases, however, people do not want to acknowledge what the evidence shows, and because they do not want to believe what the facts demonstrate, they insist the evidence cannot be true. Humans often use motivated reasoning , first deciding what is true—for example, “Gun control makes us safer” or “Gun control makes us less safe”—and then finding evidence that supports this belief while rejecting data that contradicts it. 38

Motivated Reasoning in Politics: Are Your Political Opinions as Rational as You Think?

Social psychologist Peter Ditto contrasts motivated reasoning with science, where scientists build conclusions based on evidence, and those employing motivated reasoning seek evidence that will support their pre-determined conclusions.

In other cases, individuals and interests may actually know what the facts are, but they are motivated by reasons of self-interest to deny them. The evidence is clear, for example, that nicotine is addictive and harmful to human health. The evidence is also clear that Big Tobacco, the largest cigarette companies, denied these facts for years because to admit them would have put their profits at risk. 39

Former President Donald Trump , along with many of his supporters, claims that he won the 2020 presidential election and that President Joe Biden was declared the victor only because of massive voter fraud. All attempts to prove that fraud led to Biden’s victory have failed: no evidence has been found to support Trump’s claims. 40 That these claims continue can be attributed to the fact that some individuals are simply unwilling to accept the evidence, while others benefit from denying the validity of it. 41

Empirical political science might find—based on the available evidence—that individuals with more education or more income are more likely to vote. Empirical political science would not consider whether this is good or bad; that would be a normative judgement. Empirical political scientists might explain the link between education, income, and voting by positing that better educated, more prosperous individuals are more likely to believe that their views matter and that because of that belief they are more likely to express those views at the ballot box. These political scientists might also use their findings to make a prediction: an individual with more education or higher income is more likely to vote than an individual with less education or lower income. 42

Based on this finding, empirical political scientists make no claims as to who should participate in politics. Questions about “should” are the domain of normative political science . Moral judgments cannot be made strictly on the basis of empirical statements. That members of one group vote at higher rates than another group, for example, tells us nothing about whether they deserve to vote at higher rates or whether government policies should be based more on their views as compared to those who vote at lower rates.

From this finding, however, empirical political scientists may infer a generalization. Generalizations are based on typical cases, average results, and general findings. Younger adults, for instance, typically vote less often than older adults. This does not mean that any specific young adult does not vote or that any specific older adult does, but that these statements are generally true. 43

Generalizations can be helpful in describing, explaining, or predicting, but there is a downside to generalizations: stereotyping . If the evidence shows that political conservatives in the United States are opposed to higher levels of immigration, this means neither that every conservative holds this belief nor that one must hold this belief to be conservative. If data suggests supporters of abortion rights tend to be women, it is not possible to infer from the evidence that all women seek more permissive abortion laws or that no men do. In using generalizations, it is important to remember that they are descriptive of groups, not individuals. These are empirical statements, not normative ones: they cannot by themselves be used to assign blame or credit.

Empirical political science can be used to make predictions, but predictions are prone to error. Can political science knowledge be useful for predicting the outcome of elections, for example? Yes. Given a set of rules about who is eligible to vote, how votes can be cast, and what different categories of voters believe about the candidates or policy options on the ballot, political science knowledge can be useful in predicting the outcome of the election. Our predictions might be wrong. Maybe people did not tell the truth about who they were planning to vote for. Maybe the people who said they were going to vote did not.

In 2016, most political polls predicted that Hillary Clinton would be elected president of the United States. 44 Clinton did indeed win the popular vote, as the pollsters anticipated, but Donald Trump won the electoral vote, against the pollsters’ expectations. Political science is imperfect, but it seeks to learn from and correct its mistakes. You will learn more about public opinion polling in Chapter 5: Political Participation and Public Opinion .

Many of the terms in this book, like incumbent , are relevant mainly for the study of politics. Other terms, like ceteris paribus , are useful across a broad range of studies that use the scientific method. Ceteris paribus can be translated as “all other things being equal.” If the ethnicity of a political candidate does not influence their probability of getting elected to office, ceteris paribus , if there are only two candidates and if they are alike in every relevant aspect (e.g., age, experience, ability to raise campaign funding) except their ethnicity, then the candidate’s ethnicity by itself does not affect the outcome of the election.

In real life, however, “all other things” are almost never equal. To the extent that our societies have inequalities of wealth, health, education, and other resources, the inequalities tend to be correlated—that is, mutually related—to each other. For example, wealth and health are correlated with each other in that wealthier people tend to have better health and poorer individuals tend to have poorer health. In the United States, Whites tend on average to have more wealth, health, education, and other social resources than do persons of color. 45 This does not mean that every White person is wealthier and healthier, but that on average, in general, they tend to be.

Empirical political science and political philosophy (or normative political science ) are distinct modes of inquiry. But this is not to say that they are conflicting, that one is better than the other, or that political scientists do not use both in their research. If empirical research discovers that certain groups are systematically disadvantaged in the political process, the researchers may also argue that these disadvantages are harmful or wrong and make a moral argument that the disadvantages should be reduced or eliminated. Empirical research is often inspired by normative concerns. Those who believe that human rights should be better protected may undertake research to understand the political factors that limit the protection of rights.

THE CHANGING POLITICAL LANDSCAPE

A slim majority.

The 2020 election in the United States resulted in a 50-50 split in the US Senate. 46 Until the election, the Republicans, whose 53 seats gave them a 6-seat advantage over the Democrats, were able to call the shots. With the Senate split 50-50, the US Constitution gives the vice president the power to break tie votes. Vice President Kamala Harris is a Democrat, so the Senate makeup became effectively 51-50. That one vote enormously increased the powers of the Senate Democrats. When you are in the minority, it can be difficult to move the political system in the direction you want. Once you gain the majority, getting what you want tends to be easier, at least in a democracy.

The 2020 election not only changed the balance of power in the US Senate, but it did so in an unprecedented way. The tie-breaking vote was held, for the first time in US history, by a woman and a person of color. Harris’s mother immigrated to the United States from India, and her father from Jamaica.

Political power is not a constant; the political landscape is constantly changing.

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Political Science

What this handout is about.

This handout will help you to recognize and to follow writing standards in political science. The first step toward accomplishing this goal is to develop a basic understanding of political science and the kind of work political scientists do.

Defining politics and political science

Political scientist Harold Laswell said it best: at its most basic level, politics is the struggle of “who gets what, when, how.” This struggle may be as modest as competing interest groups fighting over control of a small municipal budget or as overwhelming as a military stand-off between international superpowers. Political scientists study such struggles, both small and large, in an effort to develop general principles or theories about the way the world of politics works. Think about the title of your course or re-read the course description in your syllabus. You’ll find that your course covers a particular sector of the large world of “politics” and brings with it a set of topics, issues, and approaches to information that may be helpful to consider as you begin a writing assignment. The diverse structure of political science reflects the diverse kinds of problems the discipline attempts to analyze and explain. In fact, political science includes at least eight major sub-fields:

• American politics examines political behavior and institutions in the United States.
• Comparative politics analyzes and compares political systems within and across different geographic regions.
• International relations investigates relations among nation states and the activities of international organizations such as the United Nations, the World Bank, and NATO, as well as international actors such as terrorists, non-governmental organizations (NGOs), and multi-national corporations (MNCs).
• Political theory analyzes fundamental political concepts such as power and democracy and foundational questions, like “How should the individual and the state relate?”
• Political methodology deals with the ways that political scientists ask and investigate questions.
• Public policy examines the process by which governments make public decisions.
• Public administration studies the ways that government policies are implemented.
• Public law focuses on the role of law and courts in the political process.

What is scientific about political science?

Investigating relationships.

Although political scientists are prone to debate and disagreement, the majority view the discipline as a genuine science. As a result, political scientists generally strive to emulate the objectivity as well as the conceptual and methodological rigor typically associated with the so-called “hard” sciences (e.g., biology, chemistry, and physics). They see themselves as engaged in revealing the relationships underlying political events and conditions. Based on these revelations, they attempt to state general principles about the way the world of politics works. Given these aims, it is important for political scientists’ writing to be conceptually precise, free from bias, and well-substantiated by empirical evidence. Knowing that political scientists value objectivity may help you in making decisions about how to write your paper and what to put in it.

Political theory is an important exception to this empirical approach. You can learn more about writing for political theory classes in the section “Writing in Political Theory” below.

Building theories

Since theory-building serves as the cornerstone of the discipline, it may be useful to see how it works. You may be wrestling with theories or proposing your own as you write your paper. Consider how political scientists have arrived at the theories you are reading and discussing in your course. Most political scientists adhere to a simple model of scientific inquiry when building theories. The key to building precise and persuasive theories is to develop and test hypotheses. Hypotheses are statements that researchers construct for the purpose of testing whether or not a certain relationship exists between two phenomena. To see how political scientists use hypotheses, and to imagine how you might use a hypothesis to develop a thesis for your paper, consider the following example. Suppose that we want to know whether presidential elections are affected by economic conditions. We could formulate this question into the following hypothesis:

“When the national unemployment rate is greater than 7 percent at the time of the election, presidential incumbents are not reelected.”

Collecting data

In the research model designed to test this hypothesis, the dependent variable (the phenomenon that is affected by other variables) would be the reelection of incumbent presidents; the independent variable (the phenomenon that may have some effect on the dependent variable) would be the national unemployment rate. You could test the relationship between the independent and dependent variables by collecting data on unemployment rates and the reelection of incumbent presidents and comparing the two sets of information. If you found that in every instance that the national unemployment rate was greater than 7 percent at the time of a presidential election the incumbent lost, you would have significant support for our hypothesis.

However, research in political science seldom yields immediately conclusive results. In this case, for example, although in most recent presidential elections our hypothesis holds true, President Franklin Roosevelt was reelected in 1936 despite the fact that the national unemployment rate was 17%. To explain this important exception and to make certain that other factors besides high unemployment rates were not primarily responsible for the defeat of incumbent presidents in other election years, you would need to do further research. So you can see how political scientists use the scientific method to build ever more precise and persuasive theories and how you might begin to think about the topics that interest you as you write your paper.

Clear, consistent, objective writing

Since political scientists construct and assess theories in accordance with the principles of the scientific method, writing in the field conveys the rigor, objectivity, and logical consistency that characterize this method. Thus political scientists avoid the use of impressionistic or metaphorical language, or language which appeals primarily to our senses, emotions, or moral beliefs. In other words, rather than persuade you with the elegance of their prose or the moral virtue of their beliefs, political scientists persuade through their command of the facts and their ability to relate those facts to theories that can withstand the test of empirical investigation. In writing of this sort, clarity and concision are at a premium. To achieve such clarity and concision, political scientists precisely define any terms or concepts that are important to the arguments that they make. This precision often requires that they “operationalize” key terms or concepts. “Operationalizing” simply means that important—but possibly vague or abstract—concepts like “justice” are defined in ways that allow them to be measured or tested through scientific investigation.

Fortunately, you will generally not be expected to devise or operationalize key concepts entirely on your own. In most cases, your professor or the authors of assigned readings will already have defined and/or operationalized concepts that are important to your research. And in the event that someone hasn’t already come up with precisely the definition you need, other political scientists will in all likelihood have written enough on the topic that you’re investigating to give you some clear guidance on how to proceed. For this reason, it is always a good idea to explore what research has already been done on your topic before you begin to construct your own argument. See our handout on making an academic argument .

Example of an operationalized term

To give you an example of the kind of rigor and objectivity political scientists aim for in their writing, let’s examine how someone might operationalize a term. Reading through this example should clarify the level of analysis and precision that you will be expected to employ in your writing. Here’s how you might define key concepts in a way that allows us to measure them.

We are all familiar with the term “democracy.” If you were asked to define this term, you might make a statement like the following:

“Democracy is government by the people.”

You would, of course, be correct—democracy is government by the people. But, in order to evaluate whether or not a particular government is fully democratic or is more or less democratic when compared with other governments, we would need to have more precise criteria with which to measure or assess democracy. For example, here are some criteria that political scientists have suggested are indicators of democracy:

• Freedom to form and join organizations
• Freedom of expression
• Right to vote
• Eligibility for public office
• Right of political leaders to compete for support
• Right of political leaders to compete for votes
• Alternative sources of information
• Free and fair elections
• Institutions for making government policies depend on votes and other expressions of preference

If we adopt these nine criteria, we now have a definition that will allow us to measure democracy empirically. Thus, if you want to determine whether Brazil is more democratic than Sweden, you can evaluate each country in terms of the degree to which it fulfills the above criteria.

What counts as good writing in political science?

While rigor, clarity, and concision will be valued in any piece of writing in political science, knowing the kind of writing task you’ve been assigned will help you to write a good paper. Two of the most common kinds of writing assignments in political science are the research paper and the theory paper.

Writing political science research papers

Your instructors use research paper assignments as a means of assessing your ability to understand a complex problem in the field, to develop a perspective on this problem, and to make a persuasive argument in favor of your perspective. In order for you to successfully meet this challenge, your research paper should include the following components:

• An introduction
• A problem statement
• A discussion of methodology
• A literature review
• A description and evaluation of your research findings
• A summary of your findings

Here’s a brief description of each component.

In the introduction of your research paper, you need to give the reader some basic background information on your topic that suggests why the question you are investigating is interesting and important. You will also need to provide the reader with a statement of the research problem you are attempting to address and a basic outline of your paper as a whole. The problem statement presents not only the general research problem you will address but also the hypotheses that you will consider. In the methodology section, you will explain to the reader the research methods you used to investigate your research topic and to test the hypotheses that you have formulated. For example, did you conduct interviews, use statistical analysis, rely upon previous research studies, or some combination of all of these methodological approaches?

Before you can develop each of the above components of your research paper, you will need to conduct a literature review. A literature review involves reading and analyzing what other researchers have written on your topic before going on to do research of your own. There are some very pragmatic reasons for doing this work. First, as insightful as your ideas may be, someone else may have had similar ideas and have already done research to test them. By reading what they have written on your topic, you can ensure that you don’t repeat, but rather learn from, work that has already been done. Second, to demonstrate the soundness of your hypotheses and methodology, you will need to indicate how you have borrowed from and/or improved upon the ideas of others.

By referring to what other researchers have found on your topic, you will have established a frame of reference that enables the reader to understand the full significance of your research results. Thus, once you have conducted your literature review, you will be in a position to present your research findings. In presenting these findings, you will need to refer back to your original hypotheses and explain the manner and degree to which your results fit with what you anticipated you would find. If you see strong support for your argument or perhaps some unexpected results that your original hypotheses cannot account for, this section is the place to convey such important information to your reader. This is also the place to suggest further lines of research that will help refine, clarify inconsistencies with, or provide additional support for your hypotheses. Finally, in the summary section of your paper, reiterate the significance of your research and your research findings and speculate upon the path that future research efforts should take.

Writing in political theory

Political theory differs from other subfields in political science in that it deals primarily with historical and normative, rather than empirical, analysis. In other words, political theorists are less concerned with the scientific measurement of political phenomena than with understanding how important political ideas develop over time. And they are less concerned with evaluating how things are than in debating how they should be. A return to our democracy example will make these distinctions clearer and give you some clues about how to write well in political theory.

Earlier, we talked about how to define democracy empirically so that it can be measured and tested in accordance with scientific principles. Political theorists also define democracy, but they use a different standard of measurement. Their definitions of democracy reflect their interest in political ideals—for example, liberty, equality, and citizenship—rather than scientific measurement. So, when writing about democracy from the perspective of a political theorist, you may be asked to make an argument about the proper way to define citizenship in a democratic society. Should citizens of a democratic society be expected to engage in decision-making and administration of government, or should they be satisfied with casting votes every couple of years?

In order to substantiate your position on such questions, you will need to pay special attention to two interrelated components of your writing: (1) the logical consistency of your ideas and (2) the manner in which you use the arguments of other theorists to support your own. First, you need to make sure that your conclusion and all points leading up to it follow from your original premises or assumptions. If, for example, you argue that democracy is a system of government through which citizens develop their full capacities as human beings, then your notion of citizenship will somehow need to support this broad definition of democracy. A narrow view of citizenship based exclusively or primarily on voting probably will not do. Whatever you argue, however, you will need to be sure to demonstrate in your analysis that you have considered the arguments of other theorists who have written about these issues. In some cases, their arguments will provide support for your own; in others, they will raise criticisms and concerns that you will need to address if you are going to make a convincing case for your point of view.

Drafting your paper

If you have used material from outside sources in your paper, be sure to cite them appropriately in your paper. In political science, writers most often use the APA or Turabian (a version of the Chicago Manual of Style) style guides when formatting references. Check with your instructor if they have not specified a citation style in the assignment. For more information on constructing citations, see the UNC Libraries citation tutorial.

Although all assignments are different, the preceding outlines provide a clear and simple guide that should help you in writing papers in any sub-field of political science. If you find that you need more assistance than this short guide provides, refer to the list of additional resources below or make an appointment to see a tutor at the Writing Center.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Becker, Howard S. 2007. Writing for Social Scientists: How to Start and Finish Your Thesis, Book, or Article , 2nd ed. Chicago: University of Chicago Press.

Cuba, Lee. 2002. A Short Guide to Writing About Social Science , 4th ed. New York: Longman.

Lasswell, Harold Dwight. 1936. Politics: Who Gets What, When, How . New York: McGraw-Hill.

Scott, Gregory M., and Stephen M. Garrison. 1998. The Political Science Student Writer’s Manual , 2nd ed. Upper Saddle River, NJ: Prentice Hall.

Turabian, Kate. 2018. A Manual for Writers of Term Papers, Theses, Dissertations , 9th ed. Chicago: University of Chicago Press.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Hypothesis Examples

A hypothesis is a prediction of the outcome of a test. It forms the basis for designing an experiment in the scientific method . A good hypothesis is testable, meaning it makes a prediction you can check with observation or experimentation. Here are different hypothesis examples.

Null Hypothesis Examples

The null hypothesis (H 0 ) is also known as the zero-difference or no-difference hypothesis. It predicts that changing one variable ( independent variable ) will have no effect on the variable being measured ( dependent variable ). Here are null hypothesis examples:

• Plant growth is unaffected by temperature.
• If you increase temperature, then solubility of salt will increase.
• Incidence of skin cancer is unrelated to ultraviolet light exposure.
• All brands of light bulb last equally long.
• Cats have no preference for the color of cat food.
• All daisies have the same number of petals.

Sometimes the null hypothesis shows there is a suspected correlation between two variables. For example, if you think plant growth is affected by temperature, you state the null hypothesis: “Plant growth is not affected by temperature.” Why do you do this, rather than say “If you change temperature, plant growth will be affected”? The answer is because it’s easier applying a statistical test that shows, with a high level of confidence, a null hypothesis is correct or incorrect.

Research Hypothesis Examples

A research hypothesis (H 1 ) is a type of hypothesis used to design an experiment. This type of hypothesis is often written as an if-then statement because it’s easy identifying the independent and dependent variables and seeing how one affects the other. If-then statements explore cause and effect. In other cases, the hypothesis shows a correlation between two variables. Here are some research hypothesis examples:

• If you leave the lights on, then it takes longer for people to fall asleep.
• If you refrigerate apples, they last longer before going bad.
• If you keep the curtains closed, then you need less electricity to heat or cool the house (the electric bill is lower).
• If you leave a bucket of water uncovered, then it evaporates more quickly.
• Goldfish lose their color if they are not exposed to light.
• Workers who take vacations are more productive than those who never take time off.

Is It Okay to Disprove a Hypothesis?

Yes! You may even choose to write your hypothesis in such a way that it can be disproved because it’s easier to prove a statement is wrong than to prove it is right. In other cases, if your prediction is incorrect, that doesn’t mean the science is bad. Revising a hypothesis is common. It demonstrates you learned something you did not know before you conducted the experiment.

Test yourself with a Scientific Method Quiz .

• Mellenbergh, G.J. (2008). Chapter 8: Research designs: Testing of research hypotheses. In H.J. Adèr & G.J. Mellenbergh (eds.), Advising on Research Methods: A Consultant’s Companion . Huizen, The Netherlands: Johannes van Kessel Publishing.
• Popper, Karl R. (1959). The Logic of Scientific Discovery . Hutchinson & Co. ISBN 3-1614-8410-X.
• Schick, Theodore; Vaughn, Lewis (2002). How to think about weird things: critical thinking for a New Age . Boston: McGraw-Hill Higher Education. ISBN 0-7674-2048-9.
• Tobi, Hilde; Kampen, Jarl K. (2018). “Research design: the methodology for interdisciplinary research framework”. Quality & Quantity . 52 (3): 1209–1225. doi: 10.1007/s11135-017-0513-8

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Universities Face an Urgent Question: What Makes a Protest Antisemitic?

Pro-Palestinian student activists say their movement is anti-Zionist but not antisemitic. It is not a distinction that everyone accepts.

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By Katherine Rosman

Katherine Rosman reported from the Columbia University campus.

Follow our live coverage of the college protests at U.C.L.A. and other universities.

In a video shared widely online, a leader of the pro-Palestinian student movement at Columbia University stands near the center of a lawn on the campus and calls out, “We have Zionists who have entered the camp.”

Dozens of protesters, who have created a tent village called the “Gaza Solidarity Encampment,” repeat his words back to him: “We have Zionists who have entered the camp.”

“Walk and take a step forward,” the leader says, as the students continue to repeat his every utterance, “so that we can start to push them out of the camp. ”

The protesters link arms and march in formation toward three Jewish students who have come inside the encampment.

“It was really scary because we had like 75 people quickly gathered around, encircling us, doing exactly what he said to do,” Avi Weinberg, one of the Jewish students, said in an interview. He and his friends had gone to see the encampment, not intending to provoke, he said. When it began to feel tense, one of the students started to record the encounter. They are not sure precisely how the protest leader determined they were supportive of Israel.

“Suddenly we are being called ‘the Zionists’ in their encampment,” Mr. Weinberg said. “He put a target on our back.”

On Thursday, the incident took on new significance when a video from January resurfaced on social media showing the same protest leader, Khymani James, saying “Zionists don’t deserve to live” and “Be grateful that I’m not just going out and murdering Zionists.”

The next day, Columbia officials announced they had barred Mr. James from campus.

Columbia has been ground zero in a national student movement against Israel’s treatment of Palestinians, with protesters setting up encampments on campuses across the country. Hundreds of demonstrators — at Columbia, Yale, Emerson College, the University of Southern California and beyond — have been arrested.

Protesters occupied

Hamilton Hall early

Tuesday morning

West 114th St.

Tent encampment at

Columbia University

Faculty and staff

members guarding

access to the tents

Amsterdam Ave.

Source: Google Earth

Note: Photograph taken Monday, April 29

By Leanne Abraham; Photograph by Bing Guan

Pro-Palestinian demonstrators across the country say Israel is committing what they see as genocide against the Palestinian people, and they aim to keep a spotlight on the suffering. But some Jewish students who support Israel and what they see as its right to defend itself against Hamas say the protests have made them afraid to walk freely on campus. They hear denunciations of Zionism and calls for a Palestinian uprising as an attack on Jews themselves.

The tension goes to the heart of a question that has touched off debate among observers and critics of the protests: At what point does pro-Palestinian political speech in a time of war cross the line into the type of antisemitism colleges have vowed to combat?

If this is a matter that has vexed political leaders, university administrators and some Jewish college students, inside the encampments the very notion of antisemitism is barely discussed, in part because the demonstrators do not believe the label applies to their activism. Protest leaders point to the involvement of Jewish student activists and challenge the idea that the comfort of Israel’s supporters should be a concern.

And they draw a distinction between anti-Zionism, which describes opposition to the Jewish state of Israel, and hatred toward Jewish people in general. It is an argument many Jews see as a fig leaf for bigotry.

In a letter to Columbia students last week, university officials made clear the challenge they are facing. “We know that many of you feel threatened by the atmosphere and the language being used and have had to leave campus,” they wrote. “That is unacceptable.”

They continued, “Chants, signs, taunts and social media posts from our own students that mock and threaten to ‘kill’ Jewish people are totally unacceptable, and Columbia students who are involved in such incidents will be held accountable.”

A call for divestment

The protests beyond New York City have been inspired by the Columbia students, but they are largely diffuse, spreading via social media much like other recent movements, including Black Lives Matter and the Arab Spring.

At Columbia, the demonstration is led by a group known as CUAD — Columbia University Apartheid Divest — a coalition representing more than 100 Columbia student organizations including Students for Justice in Palestine and Jewish Voice for Peace. Leadership is amorphous. The organizers communicate on the Telegram messaging app and provide media training to the activists they make available to speak to the press.

It is unclear what financial support the group receives, and from whom. When asked, one student leader declined to comment.

But supporters from across New York have responded to the group’s Instagram pleas for water, blankets, gloves and cigarettes. Last week, Palestine Legal, an advocacy group, filed a federal civil rights complaint on behalf of the protesters, arguing that they have been subjected to anti-Palestinian and anti-Islamic harassment on campus.

Student demonstrators are specifically calling for their universities to make transparent all financial holdings and divest from companies and funds they say are profiting from or supporting Israel and its government’s policies. They also want “amnesty” for students and faculty who have been disciplined by the university as a result of their protest.

At Columbia, students are also calling on the university to end its five-year-old dual-degree program with Tel Aviv University. Some also object to the presence on the university board of Jeh Johnson, who served as homeland security secretary during the Obama administration and sits on the board of Lockheed Martin , a supplier of fighter jets to the Israel Defense Force.

Mr. Johnson declined to comment.

At encampments around the country, signs also point to the broader politics of many of the protesters. They support the anti-Israel Boycott, Divestment and Sanctions movement, which predates the war in Gaza. The students invoke historical issues of colonialism and apartheid.

Student activists who are not themselves Palestinian say that they have joined the movement for a wide variety of reasons: anguish over a humanitarian crisis in Gaza ; a rebuke of university and police response to protests; a commitment to intersectional justice where any group’s fight should be everyone’s fight; the idealistic desire to be a part of a community effort; and a sense that the fight for Palestinians is a continuation of the work started on behalf of oppressed people during the Black Lives Matter movement.

Many Jewish students taking part in the current protests say they are doing so as an expression of their Jewish values that emphasize social justice and equality. Encampments have hosted Shabbat dinners and Passover seders. At Columbia, one student said that donors have supplied kosher meals.

Samuel Law, a graduate student at the University of Texas at Austin who is Jewish and involved in the protests, was inspired by the encampments popping up around the country. “I strongly believe that the university should be there for us to care about what we care about,” he said.

‘They don’t feel safe’

Outside the pro-Palestinian encampments, the movement has drawn accusations of anti-Jewish bigotry and harassment — from political leaders as well as from some students, Jewish and not.

Jimmy Hayward, a Columbia freshman who is not Jewish, said that he has many friends studying at the Columbia-affiliated Jewish Theological Seminary who are unnerved. “I have friends in JTS that need to be walked to campus,” he said. “They want me to walk them because they don’t feel safe walking alone.”

Signs in and around the Columbia encampment include inspirational quotes, including “The world belongs to the people, and the future belongs to us,” attributed to Jiang Qing, a Chinese communist revolutionary. But there are also celebrations of violence, like “Whoever is in solidarity with our corpses but not our rockets is a hypocrite and not one of us.”

At the University of Michigan, some Jewish students said they felt rattled as they walked to class passing by protesters chanting, “Long live the intifada,” using the word for “uprising” in Arabic, which has been used to describe periods of violent protests by Palestinians against Israelis.

Tessa Veksler, a Jewish student at the University of California Santa Barbara was alarmed to see, at the school’s multicultural center, a sign on the door to a student lounge that said, “Zionist Not Allowed.”

Campus protesters dispute the notion that their movement has made pro-Israel students unsafe.

Nas Issa, a Columbia graduate who is supporting and advising protest organizers, sees a difference between feeling uncomfortable and feeling that you are in danger — “especially if you feel that your identity is tied to the practices of a particular state or to a political ideology.”

“That can be personally affecting and I think that’s understandable,” said Ms. Issa, who is Palestinian. “But I think the conflation between that and safety — it can be a bit misleading.”

When pressed, the protesters say they are anti-Zionist but not antisemitic.

It is not a distinction everyone buys.

“Let’s take any other ethnic or religious minority,” said Eden Yadegar, a junior at Columbia. “Would you only accept them if they were willing to denounce an integral part of their religious or ethnic identity? The answer is absolutely not. So how come it’s OK to say, you know, we accept Jews, but only if you denounce your religious and social and ethnic connection to your homeland? It’s ridiculous.”

Last Tuesday afternoon, Isidore Karten, an Israeli Jew, hopped a fence and entered the pro-Palestinian encampment at Columbia.

“I think it’s super important to go and show our side also,” said Mr. Karten, a 2022 Columbia graduate. “We should be allowed to be there as much as anyone else .”

Once inside, he unfurled an Israeli flag. A friend who had come with him toted a poster showing the faces and names of Israelis who were kidnapped into Gaza by Hamas on Oct. 7.

As they did, they were trailed by pro-Palestinian protesters holding a large black sheet to keep journalists from seeing them and the flag.

A few students, Mr. Karten said, chanted, “Burn Tel Aviv to the ground.”

And as he tried to talk with the demonstrators, he said, his efforts were blocked by protest leaders.

One of them was Khymani James, the student who was later barred from campus for his incendiary video. “We don’t engage with Zionists,” he said, according to Mr. Karten.

‘A wake-up call’

Mr. James’s video , which was publicized by a right-wing outlet on Thursday and then reported on by The New York Times and others, drew wide attention, including from President Biden, whose spokesman issued a statement saying, “These dangerous, appalling statements turn the stomach and should serve as a wake-up call.”

Others cautioned not to use the words of one activist to define a much larger group.

The Rev. Michael McBride , a founder of Black Church PAC, who has pressed for a cease-fire in Gaza, said Mr. James’s comments were not representative of the antiwar movement.

“You can go to a protest and find anything you’re looking for,” said the Rev. McBride, who leads a church in Berkeley, Calif. “If you’re looking for that, then you’ll find it.”

At Columbia, the CUAD student protest organization on Friday posted a statement on Instagram that said, “Khymani’s words in January do not reflect his view, our values, nor the encampment’s community agreements.” The statement added, “In the same way some of us were once Zionists and are now anti-Zionists, we believe unlearning is always possible.”

But for university administrators, Mr. James’s case has presented a serious challenge.

He made some of his comments about killing Zionists — including that “taking someone’s life in certain case scenarios is necessary and better for the overall world” — during a college disciplinary hearing in January.

But he was not barred from campus until the January video began to spread last week. A notification sent to Mr. James by the university and shared with The New York Times by one of his friends described it as an “interim suspension.” Mr. James, who said in a statement last week that his words were “wrong,” could not be reached for comment.

“When leadership learned of the video, it took immediate steps to ban James from campus,” a Columbia spokesman said this weekend. “We initiated disciplinary proceedings which encompass this and additional potential violations of university policies.”

It is not clear whether the Columbia administrator conducting the disciplinary hearing alerted a superior or public safety official to Mr. James’s remarks at the time — or whether Columbia policy dictated that the administrator should have.

A spokesman for the university declined to comment further.

The episode left Avi Weinberg, the pro-Israel student who was surrounded by Mr. James and other protesters at the encampment, distressed. “The university was aware that this is his mind-set, and the university put their students in danger,” he said. “That is very present on my mind.”

Eryn Davis, Neelam Bohra, Katie Glueck, Stephanie Saul, Olivia Bensimon and Karla Marie Sanford contributed reporting.

Katherine Rosman covers newsmakers, power players and individuals making an imprint on New York City. More about Katherine Rosman

Our Coverage of the U.S. Campus Protests

News and Analysis

President Biden broke days of silence to finally speak out on the unrest disrupting campuses  across the United States, denouncing violence and antisemitism even as he defended the right to peaceful dissent.

At the University of California, Los Angeles, police officers dismantled a pro-Palestinian encampment  and made arrests after a tense hourslong standoff with demonstrators.

Police officers in riot gear arrested pro-Palestinian demonstrators at Fordham University’s Manhattan campus , the third university in New York City to face mass arrests.

Choosing Anonymity:  In an online world, doxxing and other consequences have led many student protesters to obscure their identities by wearing masks and scarves. That choice has been polarizing .

Seeing Links to a Global Struggle:  In many student protesters’ eyes, the war in Gaza is linked to other issues , such as policing, mistreatment of Indigenous people, racism and climate change.

Ending the Unrest:  Across the nation, universities are looking for ways to quell the protests . Columbia has taken the spotlight after calling in the police twice , while Brown chose a different path .

A 63-Year-Old Career Activist:  Videos show Lisa Fithian, whom the police called a “professional agitator,” working alongside protesters at Columbia  who stormed Hamilton Hall.

Empirical Methods in Political Science: An Introduction

By Justin Zimmerman

9.1 Introduction

The field of political science has traditionally focused on the importance of hypothesis testing, causal inference, experiments and the use of large n data. Quantitative methods in all its capacities is without a doubt important, but what can be lost at times is the value of small n methods of inquiry within the field of political science. Researchers such as Kathy Kramer, Cathy Cohen, Reuel Rogers, and Jennifer Hochschild et. al. have all used small n methods to tell stories about particular groups that have rarely been highlighted in political science. Whether its identifying rural consciousness in Wisconsin ( Kramer 2016 ) , researching the secondary marginalization of the most disfranchised in the black community ( Cohen 1999 ) , explaining the unique political stances of Afro-Caribbean immigrants ( Rogers 2006 ) , or highlighting the politics of a new racial order ( Hochschild, Weaver, and Burch 2012 ) , small n data can allow for a researcher to discover new information not easily attainable through quantitative methods alone. Small n methods allow for a more in depth assessment of a particular area and people.

This chapter will focus on the importance small n research. The chapter will highlight the various methods for conducting small n research including: interviews, participant observation, focus groups, and process tracing, as well as the various procedures for determining case selection. First, the chapter will elaborate the differences and goals of small n research as compare to quantitative research.

9.2 Background

To be a well-rounded political scientist it is important to understand that not every question can be answered through quantitative methods alone. There are times when small n methods are the more appropriate option. Yet, how does a researcher decide when small n methods are appropriate for their research? The researcher must be able to identify the differences and purposes of small n qualitative research and quantitative research. First, quantitative research focuses on the effects of causes, while qualitative methods is focused on the causes of effects. In other words, quantitative research, especially with regards to causal inference, aims to figure out if a particular treatment causes a particular outcome, such as an increase in an individual’s education causes them to be more political mobilized.

Small n qualitative research on the other hand focuses on understanding how the outcome came to be. American Political Development (APD) scholars are a great reference to this line of thinking. APD scholars look to track why certain outcomes came to be, such as Paul Frymer’s work on Western expansion in the United States of America ( Frymer 2017 ) or Chloe Thurston’s research on housing policy and how it has historically discriminated against women, African Americans, and the poor through the use of public-private partnerships ( Thurston 2018 ) . Small n qualitative research also includes oral histories such as those provided by Yolande Bouka concerning the Rwandan genocide ( Bouka 2013 ) and the interviews and historical context to explain the coercive power of policing in Latin America as researched by Yanilda María González ( González 2017 ) . In short, small n qualitative research aims to tell a story of how an event or policy came to be, and what are the experiences of particular groups because of a particular event or policy.

Thus, a small n qualitative researcher must take care to ensure their work is able to satisfy three characteristics of good qualitative research. First, their research must emphasize the cause and the implications it has. Second, good small n qualitative theories must explain the outcome in all the cases within the population. Lastly, qualitative questions must answer whether events were necessary or sufficient for an outcome to occur, with the cause providing the explanation. To setup qualitative research it is important to that understand that qualitative methods are interested more in the mechanisms behind things. Small n approaches can help us explore the underlying process such as how institutions evolve and change by gathering data about institutions, but it can also be answered through looking at institutional change in one or two contexts. Small n qualitative research can be inductive as a researcher builds the theory and hypotheses from the data, or deductive by testing theories and hypotheses with the data. What is critical in building qualitative research whether inductively or deductively is case selection.

9.3 Case Selection

Case selection for small n qualitative research setup to use a small number of cases in order to go into a deep dive into a specific subject. For instance, a researcher may use a specific neighborhood to explain a specific political characteristic of the community. Reuel Rogers conducts this exact research when he interviewed Afro-Caribbean residents in New York City about their political preferences as new immigrants of the United States of America (2006). This case selection allowed for Rogers to assess the veracity of an age old claim that pluralism allows for immigrants to eventually assimilate into American culture and government participation by highlighting the complexity that comes from immigrants that are identified as black. Rogers finds that Afro-Caribbean immigrants suffer from discrimination that may hinder their ability to assimilate into American society. Yet, how does a researcher decide what cases to use? Seawright and Gerring provide some insight by identifying seven case selection procedures ( Seawright and Gerring 2008 ) . For the purposes of this text, this chapter will focus on four of these case selection procedures. The cases focused on will be most similar, most different, typical, and deviant. The chapter will also briefly describe extreme, diverse, and influential cases.

9.3.1 Most Similar

Seawright and Gerring instruct the use of the most similar case selection must have at least two cases to compare. Ideally, when using most similar cases all independent variables other than the key independent variable or dependent variable would be similar. For example, we may compare neighborhood with similar variables for income, religion, and education with the key independent variable such as race being the only difference. Thus, a researcher could use small n case selection to research differences or similarities that black middle class residents of particular neighborhood have with a white middle class neighborhood. It should be noted that matching any particular cases by exact characteristics is essentially impossible in the social science. Thus, this technique is daunting to say the least. Yet, part of the compromise of political science and social science in general is doing the best with the information you have and being honest about the limitations. This is especially important in the use of the most similar case selection procedure.

9.3.2 Most Different

Gerring and Seawright also identify the use of the most different case selection procedure. The most different case refers to cases that are different on specified variables other than the key independent variable and dependent variable. For instance, maybe there are class, education, and religion differences between two neighborhoods, but the key independent variable of race remains the same for both. Gerring and Seawright argue that this tends to be the weaker route to take in comparing two case but nonetheless it is an option to use for a small n researcher under the right circumstances.

9.3.3 Typical Case

The typical case refers to common or representative case that a theory explains. According to Gerring and Seawright, the typical case should be well defined by an existing model which allows for the researcher to observe problems within the case rather than relying on any particular comparison. A typical case is great for confirming or disconfirming particular theories. Referring back to the work of Reuel Rogers and his work on black Caribbean immigrants in New York City, Rogers was able to disconfirm Dahl’s argument on plurality allowing for the eventual full inclusion of immigrants by pointing to the racism and discrimination black Caribbean immigrants face that hinders their ability to be fully incorporated into the American polity. What is most important for understanding the typical case is that it is representative and that this representation must be placed somewhere within existing models and theories to be useful.

9.3.4 Deviant Case

Conversely to the typical procedure, the deviant case cannot be explained by theory. A researcher can have one or more deviant cases and these cases serve more as a function of exploration and confirming variation within cases. The deviant case is essentially checking for anomalies within an established theory and allows for the finding of previously unidentified explanations in particular cases. An example may be finding that liberalism is defined differently depending on certain populations which runs counter to Haartz’ assertion that liberalism assumes a certain amount of unity throughout the country. What is most important for understanding the deviant case is for a researcher to check for representativeness of a theory, which allows for much of the value of small n methods. A researcher can tell a story of a particular group that is often assumed to fit the general understandings of political science but through the use of qualitative methods is shown to be more complex than previously understood.

9.3.5 Other Selection Approaches

Along with the four main case selection procedures are other are three other approaches worth noting. The first being the extreme case . The extreme case is characterized by cases that are very high or very low on a researchers’ key independent or dependent variables. It can provide the means to better understand and explore phenomena through the means of maximizing variation on the dimensions of interest in the selection of very low and high cases (Seawright and Gerring, 2008). Unlike in linear regression, where extreme values can provide an incomplete or inaccurate picture, in small n approaches, extreme cases can offer the opportunity for deepening the understanding of a phenomenon by focusing on its most extreme instances. (Collier, Mahoney and Seawright 2004; 4-5)

Second, diverse cases highlight range of possible values. A researcher can choose low/medium/high for their independent variable to illustrate the range of possibility. Two or more cases are needed and this procedure mainly serves as a method for developing new hypotheses. These cases are minimally representative of the entire population

Lastly, influential cases are outliers in a sense that they are not typical and may be playing an outsize role in a researcher’s results. It is unlikely that small n methods will play a significant role as influential cases rely on large n methods.

Check-in Question 1: How should a researcher go about choosing a case selection procedure?

9.4 Method: setup/overview

Small n methods are characterized by an emphasis on detail. A researcher has to be able to see the environment that they are studying. The purpose of small n methods is to gain an in depth knowledge of particular cases. Field notes will be a researcher’s best friend. A researcher should take notes on the demographics, noises, emotions, mores, and much more to gain an accurate understanding of the population they are studying. Additionally, small n methods are about building rapport with the population being studied and constantly taking into account one’s own biases and thoughts as they conduct fieldwork. It is not uncommon for researchers to eventually live in the places they are studying. During her work on the black middle class, Mary Pattillo would eventually move into the South Side Chicago neighborhood of Groveland. The neighborhood was the subject of her book Black Picket Fences ( Pattillo 2013 ) . Pattillo would attend community meetings, shop, and cultivate lasting relationships with the community, which would guide her research. There is a level of intimacy needed to do good small n research. Not always to the extent of needing to live with one’s participants, but still a need for insight that goes beyond a shallow understanding of a particular community. Small n qualitative researcher gets at these insights through several methods.

Note: Take sometime to think about for your own research what you are noticing during your fieldwork? How is this informing your study?

9.5 Method: types

The typical methods used in small n research are interviews, participant observation, focus groups, process tracing, and ethnography. Each method has its advantages and disadvantages and a researcher can utilize more than one these methods depending on the aims of their research. In deciding on a small n method a researcher must consider the goals of the research, validity, and conceptual framework that will feed the researcher’s broader question. The diagram below illustrates that a small n qualitative researcher should be purposeful in their research design. They must consider their overall question. Specify the goals of their research, consider the theories that are driving the conceptual framework of their research, and consider the validity (does it make sense) of their research design.

Figure 9.1: Research Methods Diagram

Focusing on the methods portion of the diagram, this chapter will discuss in further detail each small n qualitative method.

9.5.1 Interviews

Conducting interviews can seem like a daunting experience. A researcher has to develop a comfort in approaching diverse sets of people, many times in unfamiliar environments. A researcher has to be able to build rapport, get their questions answered within a limited amount of time and encourage the participant to elaborate and clarify answers. Interviews are challenging but the good news is there are ways to make the process smoother through organization, commitment, and earnestness.

Before contacting anyone for an interview, a researcher should take sometime to organize their interview guide and decide whether they want to conduct structured or semi-structured interviews. The interview guide highlights the questions and themes the researcher plans to cover during the interview. The format of the interview guide is determined by whether the researcher has a rigid structure of questions they plan to ask each participant (Structured Interview) or a more flexible interview strategy that allows for the researcher to deviate from questions and allow for a more exploratory conversation within the confines of the research question (Semi-Structured Interview).

Once a researcher has decided on an interview structure and completed their interview guide, they can decide who they want to recruit to participate in the interview. The researcher will need to consider the key informants and representative sample they want to recruit. Key informants are experts that can discuss the population of interest including but not limited to academics, community leaders, and politicians. The representative sample is the population that your research is based on. For example, Wendy Pearlman’s text We Crossed a Bridge and it Trembled: Voices from Syria has a representative sample of Syrians displaced during the civil war ( Pearlman 2017 ) . What is important to understand about the difference between the representative sample and key informants is that the sample is giving a firsthand account of their experiences, while a key informant is mainly given their observation and experiences of the representative sample from an outside perspective.

Moving on to recruitment, Robert Weiss’ Learning From Strangers lists several reasons that affect whether an individual is willing to participate in an interview including: occupation, region, retirement status, vulnerability, and sponsorship from others within their network ( Weiss 1994 ) . Unfortunately, there is no easy way to recruit but from experience face to face discussions with potential participants and immediate follow up are quite effective. Also use snowball sampling to use previous participants acquaintances and networks to participate in interviews. These strategies are not full proof but a layer of personal interaction through face to face contact or networks does have advantages in making many people more receptive to participating in interviews.

Lastly, when the day to interview finally arrives a researcher should have two recorders, tissue, interview guide, consent form, and a gift card for the participant if possible. The interview should not take any longer than an hour as a sign of respect for the time of your participant. A researcher should take meticulous notes during the interview. Also, the researcher must gain the permission of the participant to conduct a follow up interview if necessary.

Check-in Question 2: What is this difference between a representative sample and a key informant?

9.5.2 Participant Observation

Participant observation is a variation of ethnographic research where the researcher participates in an organization, community, or other group-oriented activities as a member of the community. Typically used in anthropology, it involves a researcher immersing themselves within a community. Participant observation requires that the research build a strong bond of trust with the observed community. A researcher (with the help of IRB) will need to decide if participation will be active or passive and whether it should be overt or covert. This can be a particularly sticky situation, as a passive and covert observation may mean community members have no idea they are being studied, while active and overt participation can lead to the environment changing as the community is aware of the presence and role of the researcher. Referring back to the work of Mary Pattillo, recall that she eventually became a citizen of Groveland and participated as any other citizen in community activities ( Pattillo 2013 ) . This included leading the local church choir, joining the community’s local action group, and coaching cheerleading at the local park. Pattillo saw her participant observations as essential to describing the black middle class in Groveland and even speaks of the parallels between the Groveland neighborhood and her upbringing in Milwaukee.

The key purpose of participant observations is to provide deeper insight into process and how things function. This exercise is good for ‘theory building,’ but it may be best to include another method, such as interviewing, to allow for the community to tell their story as well, a supplemental method Pattillo uses as well. What is most important when using participant observation (in qualitative methods in general) is to take meticulous field notes with attention to accuracy. A researcher should be cognizant of their own biases and constantly thinking through their analysis to make sure they a capturing an accurate story. In order to tell an accurate story a researcher should keep both mental notes and a notepad. After the end of an event it is important to write everything down while the researcher’s memory is fresh.

Check-in Question 3: What are the advantages and disadvantage of covert and over participant observation?

9.5.3 Focus Groups

Focus Groups, similar to individual interviews requires a researchers to set questions, recruit participants and follow up with participants as necessary. As with an individual interview, the researcher should have an interview guide to help structure the questions and themes of the focus group. The advantage of a focus group is that a researcher is able to facilitate multiple respondents at once, which can lead to additional details and information you might not get in series of single interviews. As seen in Melissa Harris Perry’s Sister Citizen , focus groups are great for spurring discussion about topics such as stereotypes ( Harris-Perry 2011 ) . A researcher should note impressions, points of contention, and general interactions within the group. Group dynamics and discussions can be used for theory building as well as getting a deeper understanding of a particular group of people.

9.5.4 Process Tracing

Process tracing is a method of causal inference using descriptive inference over time. Notably used by APD scholars, the goal of process tracing are to collect evidence to evaluate a set of hypotheses through the framing of historical events. There are four tests when discussing process tracing.

The first is the straw in the wind test . The straw in the wind test can increase plausibility but cannot determine that any event necessary nor sufficient criterion for rejecting. It can only weaken hypotheses. The hoop test establishes necessary criterion. Though the hoop test does not confirm any particular hypotheses, the test can eliminate hypotheses. The smoking gun test provides a sufficient but not necessary criterion for hypotheses. The test can give strong support for a given hypothesis and can substantially weaken competing hypotheses. Lastly, the doubly decisive test illustrates evidence that is necessary sufficient. Necessary being when the necessary causes occur when the effect occur and sufficient being when causes always occur after effects.

What is important to understand about process tracing beyond the numerous tests is that process tracing is a good way in political science to draw evidence for certain events and phenomena. Chloe Thurston uses process tracing to track the development of the public-private partnership with regards to housing policy ( Thurston 2018 ) . Through numerous historical text including archives, testimonial, and presidential records, Thurston is able to develop a story of how public-private partnerships led to home owning policies that discriminated according to gender, race, and socioeconomic status and how advocacy groups were able to combat these policies.

Thus, process tracing looks for historical evidence to explain certain events or policies.

9.5.5 Ethnography

Ethnography involves studying groups of people and their experiences ( Emerson, Fretz, and Shaw 2011 ) . As mentioned earlier with participant observations, the purpose of ethnography is for a researcher to immerse themselves in the environment they are studying. The researcher will need to develop relationships with the community and detail the environment through constant note taking and reflection. This is reflected in the work of many of the researchers already detailed in the chapter. Done correctly a researcher can document the emotions, attitudes, and relationships in a community that are sometimes impossible to capture in quantitative work.

In his text Wounded City: Violent Turf Wars in a Chicago Barrio , Robert Vargas is able to capture the fear, frustration, and empowerment felt by the residents of Chicago’s Little Village as they negotiate turf wars between gangs, police, and alderman [vargas2016a]. The insight he is able to gather cannot simply be surveyed, but must be observed in the environment in order to develop trust within the community.

Ethnography is about relationship building and allows for latent findings that may give proper context for understanding particular groups. This is especially important for underrepresented communities, where in depth research is often lacking and responsiveness to a survey may not be likely under less personal circumstances. Ethnography allows a researcher to take a more holistic approach in understanding a community.

Check-in Question 4: What should a researcher be looking for when taking ethnographic field notes?

9.6 Applications

The application of small n qualitative methods is based on a researcher’s question. Sociologist, Celeste Watkins-Hayes, explains that qualitative research is meant to tell specific stories about a community. Going back to the diagram displayed in the beginning of the chapter, a researcher should think of the story they are trying to tell and goals, whether the small n qualitative methods they want to use are valid, and how does all of this relate to the research question. Most importantly when applying small n qualitative methods, record keeping is of the utmost importance. A researcher should make sure that their field notes are detailed and capture an accurate depiction of the environment of study. This means not only self-reflecting on one’s own biases, but also using multiple small n and quantitative methods when appropriate to tell the most complete story possible. Lastly, a researcher needs a method of coding the themes and messages found through their study. Recording encounters and taking good field notes will go far in creating an organized system, which will allow for a researcher to tell an accurate story that captures the nuances and characteristics of a particular community.

9.7 Advantages of Method

Small n qualitative research thrives with gaining in depth information about a limited number of cases. This will allow a researcher to provide insight of a small number of communities that may be missing from large n studies. In this same breath, small n methods allow for theory building that many times is unique to many of the lessons taken for granted in the discipline of political science. It is one thing to ask an individual participant to check an answer on a question about immigration, race, or president. Yet, there is value is going deeper and wrestling with the values, contradictions, as well as the historic and present-day context that make up the politics of a particular people. It is through small n methods that researchers are able to get a better understanding of topics such as rural consciousness, neighborhood violence, and linked-fate. Small n methods allow a researcher to tell the stories that are often ignored, unheard, or misinterpreted through other methods.

9.8 Disadvantages of Method

The major disadvantage of small n methods is that a researcher is working from a small pool. This should not be confused with having less data. Interviews, field notes, and archives bring an abundance of data but the sources are limited. A responsible researcher will have to consider whether their case selection is representative of the broader community and how best to ensure that they are getting a diverse set of voices to hear from to avoid inaccurate assessments of a community. Thus, it is difficult (but not impossible) to generalize from the use of small n research. A researcher including quantitative methods or multiple small n methods in their study will go a long way in strengthening their arguments.

9.9 Broader significance/use in political science

As has been noted numerous times in the chapter, small n qualitative methods allow a researcher to explore groups that cannot necessarily be understood merely with a survey, experiment, or causal inference. Small n allows for a researcher to go into more detail about groups that cannot be fully understood through quantitative research either because they are too small or too unresponsive to quantitative methods. Additionally, small n qualitative research also allows for political scientist to consider context and history when developing claims regarding the political behaviors and institutions that shape society. This context can help a political scientist go beyond superficial understandings of particular groups. For instance, Michael Dawson’s text Black Visions uses quantitative methods to show that African Americans have a high support for Black Nationalism ( Dawson 2001 ) . This finding alone could be taken as example of mass black prejudice, as Black Nationalism has been associated most notably with the bigoted views of Louis Farrakhan. Yet, Dawson takes care to include the historical context, including testimonials by leading black thinkers, detailing the long history of debate concerning Black Nationalism, as well as the economic violence and discrimination committed against the black community, which leads to support of some forms of Black Nationalism. Small n qualitative research through the use of history, interviews, and ethnography allows for the telling of these stories, adding complexity and nuance to many of political science’s well established theories and perceptions.

9.10 Conclusion

Not all questions can be answered with a survey and experiment alone. Sometimes a deeper study into a community and event can lead to new and exciting insights in the discipline of political science. Admittedly, small n qualitative research can be met with some cynicism in certain parts of the political science community, but when done correctly through meticulous note taking, coding, and preparation small n qualitative methods can provide insights that have yet to be fully articulated in the discipline and assist in answering some of the most important questions of the day including policing, immigration, and race relations.

9.11 Application Questions

Application Question 1

What are some materials needed to conduct small n research?

Application Question 2

When in the field, how does a researcher build rapport with the community?

9.12 Key Terms

NOTE: this is an incomplete list and it needs expanded!!!!!

covert observation

deviant case

diverse cases

ethnography

extreme case

focus groups

influential cases

key informant

most different

most similar

overt observation

participant observation

process tracing

representative Sample

snowball sampling

smoking gun test

straw wind test

typical case

9.13 Answers to Application Questions

A researcher should have their interview guide prepared, tissues, and two recorders if conducting interviews or focus groups. Additionally, a researcher should have a notepad for field notes and consent forms if necessary. Business cards are also useful when trying to recruit participants from the field.

Rapport can be built through appearance including dress, race, gender, regional, and class markers. Most importantly, a researcher should present themselves as engaged and attentive to the participants. A researcher should remain professional and read the room, rapport building for a group of blue collar workers may be different than with college students. A researcher should remain cognizant of this distinction and look for openings to build connections when possible.

Department of Political Science

“The Political Rhetoric of Christian Sermons across Traditions,” Paul Lendway, Yale

AMERICAN POLITICS & PUBLIC POLICY WORKSHOP

Abstract: Why do evangelicals have stronger voter support for Trump relative to other Christian groups? This paper presents and tests a theory for how variation in sermon content can predispose evangelicals, relative to non-evangelicals, to have greater support for conservative politicians. An analysis of a novel random sample of sermons from across the United States finds compelling support for this theoretical framework.

Paul Lendway is a fifth-year Ph.D. candidate in political science at Yale University studying inequality, populism, and social movements. His research has been published in American Politics Research, Environmental Politics, and the Yale Journal of International Affairs. He has presented his research at a wide range of organizations, including the American Political Science Association, Harvard University, the University of Pennsylvania, and Yale University. He is a Lead Editor for the Yale Journal of Health Policy, Law, and Ethics, a Content Editor for the Yale Journal of International Affairs, and a Visiting Editor for Princeton’s Journal of Public and International Affairs.

Open only to current members of the Yale community. Please visit this link to subscribe and receive regular announcements: https://csap.yale.edu/american-politics-public-policy-workshop .

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Epigenomic analysis sheds light on risk factors for ALS

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For most patients, it’s unknown exactly what causes amyotrophic lateral sclerosis (ALS), a disease characterized by degeneration of motor neurons that impairs muscle control and eventually leads to death.

Studies have identified certain genes that confer a higher risk of the disease, but scientists believe there are many more genetic risk factors that have yet to be discovered. One reason why these drivers have been hard to find is that some are found in very few patients, making it hard to pick them out without a very large sample of patients. Additionally, some of the risk may be driven by epigenomic factors, rather than mutations in protein-coding genes.

Working with the Answer ALS consortium, a team of MIT researchers has analyzed epigenetic modifications — tags that determine which genes are turned on in a cell — in motor neurons derived from induced pluripotent stem (IPS) cells from 380 ALS patients.

This analysis revealed a strong differential signal associated with a known subtype of ALS, and about 30 locations with modifications that appear to be linked to rates of disease progression in ALS patients. The findings may help scientists develop new treatments that are targeted to patients with certain genetic risk factors.

“If the root causes are different for all these different versions of the disease, the drugs will be very different and the signals in IPS cells will be very different,” says Ernest Fraenkel, the Grover M. Hermann Professor in Health Sciences and Technology in MIT’s Department of Biological Engineering and the senior author of the study. “We may get to a point in a decade or so where we don’t even think of ALS as one disease, where there are drugs that are treating specific types of ALS that only work for one group of patients and not for another.”

MIT postdoc Stanislav Tsitkov is the lead author of the paper , which appears today in Nature Communications .

Finding risk factors

ALS is a rare disease that is estimated to affect about 30,000 people in the United States. One of the challenges in studying the disease is that while genetic variants are believed to account for about 50 percent of ALS risk (with environmental factors making up the rest), most of the variants that contribute to that risk have not been identified.

Similar to Alzheimer’s disease, there may be a large number of genetic variants that can confer risk, but each individual patient may carry only a small number of those. This makes it difficult to identify the risk factors unless scientists have a very large population of patients to analyze.

“Because we expect the disease to be heterogeneous, you need to have large numbers of patients before you can pick up on signals like this. To really be able to classify the subtypes of disease, we’re going to need to look at a lot of people,” Fraenkel says.

About 10 years ago, the Answer ALS consortium began to collect large numbers of patient samples, which could allow for larger-scale studies that might reveal some of the genetic drivers of the disease. From blood samples, researchers can create induced pluripotent stem cells and then induce them to differentiate into motor neurons, the cells most affected by ALS.

“We don’t think all ALS patients are going to be the same, just like all cancers are not the same. And the goal is being able to find drivers of the disease that could be therapeutic targets,” Fraenkel says.

In this study, Fraenkel and his colleagues wanted to see if patient-derived cells could offer any information about molecular differences that are relevant to ALS. They focused on epigenomic modifications, using a method called ATAC-seq to measure chromatin density across the genome of each cell. Chromatin is a complex of DNA and proteins that determines which genes are accessible to be transcribed by the cell, depending on how densely packed the chromatin is.

In data that were collected and analyzed over several years, the researchers did not find any global signal that clearly differentiated the 380 ALS patients in their study from 80 healthy control subjects. However, they did find a strong differential signal associated with a subtype of ALS, characterized by a genetic mutation in the C9orf72 gene.

Additionally, they identified about 30 regions that were associated with slower rates of disease progression in ALS patients. Many of these regions are located near genes related to the cellular inflammatory response; interestingly, several of the identified genes have also been implicated in other neurodegenerative diseases, such as Parkinson’s disease.

“You can use a small number of these epigenomic regions and look at the intensity of the signal there, and predict how quickly someone’s disease will progress. That really validates the hypothesis that the epigenomics can be used as a filter to better understand the contribution of the person’s genome,” Fraenkel says.

“By harnessing the very large number of participant samples and extensive data collected by the Answer ALS Consortium, these studies were able to rigorously test whether the observed changes might be artifacts related to the techniques of sample collection, storage, processing, and analysis, or truly reflective of important biology,” says Lyle Ostrow, an associate professor of neurology at the Lewis Katz School of Medicine at Temple University, who was not involved in the study. “They developed standard ways to control for these variables, to make sure the results can be accurately compared. Such studies are incredibly important for accelerating ALS therapy development, as they will enable data and samples collected from different studies to be analyzed together.”

Targeted drugs

The researchers now hope to further investigate these genomic regions and see how they might drive different aspects of ALS progression in different subsets of patients. This could help scientists develop drugs that might work in different groups of patients, and help them identify which patients should be chosen for clinical trials of those drugs, based on genetic or epigenetic markers.

Last year, the U.S. Food and Drug Administration approved a drug called tofersen, which can be used in ALS patients with a mutation in a gene called SOD1. This drug is very effective for those patients, who make up about 1 percent of the total population of people with ALS. Fraenkel’s hope is that more drugs can be developed for, and tested in, people with other genetic drivers of ALS.

“If you had a drug like tofersen that works for 1 percent of patients and you just gave it to a typical phase two clinical trial, you probably wouldn’t have anybody with that mutation in the trial, and it would’ve failed. And so that drug, which is a lifesaver for people, would never have gotten through,” Fraenkel says.

The MIT team is now using an approach called quantitative trait locus (QTL) analysis to try to identify subgroups of ALS patients whose disease is driven by specific genomic variants.

“We can integrate the genomics, the transcriptomics, and the epigenomics, as a way to find subgroups of ALS patients who have distinct phenotypic signatures from other ALS patients and healthy controls,” Tsitkov says. “We have already found a few potential hits in that direction.”

The research was funded by the Answer ALS program, which is supported by the Robert Packard Center for ALS Research at Johns Hopkins University, Travelers Insurance, ALS Finding a Cure Foundation, Stay Strong Vs. ALS, Answer ALS Foundation, Microsoft, Caterpillar Foundation, American Airlines, Team Gleason, the U.S. National Institutes of Health, Fishman Family Foundation, Aviators Against ALS, AbbVie Foundation, Chan Zuckerberg Initiative, ALS Association, National Football League, F. Prime, M. Armstrong, Bruce Edwards Foundation, the Judith and Jean Pape Adams Charitable Foundation, Muscular Dystrophy Association, Les Turner ALS Foundation, PGA Tour, Gates Ventures, and Bari Lipp Foundation. This work was also supported, in part, by grants from the National Institutes of Health and the MIT-GSK Gertrude B. Elion Research Fellowship Program for Drug Discovery and Disease.

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