Maybe you’ve found a great quantitative social science journal article that seems interesting, but the structure and language is perhaps difficult or overwhelming. Below are some general strategies and commonly used vocabulary that should make the process easier.

The guide is set up with three primary sections — the set up of social science papers, how to strategically read through the papers (and what to look for), and a vocabulary list. We also describe why quantitative and qualitative papers differ slightly.  These sections are included below:

The set up:

  • Abstract – This is a short, one paragraph overview of the paper. It will describe the general problem the paper is tackling, how they will examine it, and the general take-aways from the paper.
  • Introduction – This section introduces the paper, giving a general taste of the literature discussed, the concepts used, and where this paper fits into the broader academic discussion.
  • Literature Review – These sections are rarely actually called “Literature Review,” but it’s the place where the authors review the literature around the concepts discussed in the paper. This section tends to have a lot of citations of previous literature, and it will work to explain the state of the field around the paper’s topic and where this paper fits. This section is often ended with a review of the research question or hypotheses for the paper.
  • Data – This section discusses the data being used. There are generally two different types of data: 1) data that the authors collected, such as through developing their own survey or an experiment; 2) data that the authors were allowed to use that others developed, such as major nation-wide surveys like the General Social Survey.
  • Findings – This section walks through any statistical techniques that were used in the study, and examines the findings. This section also tends to have tables of statistical output, that may be difficult to understand without statistical training.
  • Discussion/Conclusion – This is the end of the paper, where the authors explain what the study proposed to find, and what the findings were. This section also describes the broader implications of this study for the academic field. Papers will sometimes just have a “discussion” section or sometimes just have a “conclusion” section — or sometimes have both.


Best practices about reading an academic paper:

Step 1: Read the abstract. This will provide a general punchline for the paper, and can help you to understand key words you should look out for. You generally want to be able to answer the following prompt: “You might think X, but really it’s Y,” by the end of the paper. The abstract is a good place to figure out what academics thought would be true, versus what this paper finds to be true.

Step 2: Look through the paper. Check for section headings and try to get a feel for the general topic and what the authors are highlighting in the paper.

Step 3: Skim the conclusion. Look through the conclusion to see what the paper found and generally what the paper contributes to a broader academic discussion.

Step 4: Read the introduction. Identify the research question or hypothesis (papers will generally have one or the other), as well as the Independent Variable(s) and Dependent Variable(s). What are the authors suggestion affects something else? Identify what is motivating the research question — why do we care about this particular issue? Identify any key terms in the article, particularly jargon or general terms that you think may have specific meanings within that context, and look them up (or at least, keep an eye out in the text for broader context clues).

Step 5: Skim the literature review. For our purposes, you don’t need to necessarily understand every argument that is going on within the literature in regards to the concepts discussed in the paper — you want a general overview. The literature review provides a lot of background information that may not be as useful, but if you plan to do more research or want citation suggestions, the literature review and list of works cited is a good place to start.

Step 6: Read the data and findings sections. Look at how the authors performed the study, in particular try to match the concepts they are using with the variables they use, or the “operationalization” of the concepts. Are they interested in examining A, but are using variable B to study it? That can be a red flag. Researchers can be limited by their data sources, particularly if they’re using a nationally-representative survey they had no part in designing. But that doesn’t negate bad research design. The findings section will often include tables, but without statistical training, they are often confusing. The findings section should also outline, in words, the findings on those tables. Often, that discussion is framed in terms of the research question or hypotheses explicitly, which is helpful for the reader. The findings section will be the place where the authors explain the findings, so work to read it as carefully as you can. The findings section also often includes a lot of statistical jargon, which can be confusing.

Step 7: Read the conclusion/discussion. I know you already skimmed it, but now that you know what the concepts are, how they were studied, and what the findings are, you should be able to see those findings revealed in the conclusion! Plus, the authors generally add more information about how this fits with other literature in the field and extensions of this paper for future research.



  • Descriptive Statistics – This is usually displayed in a table of all of the variables being used, showing the mean, standard deviation, and minimum and maximum values. The bottom of the descriptive statistics table also includes the number of respondents in the sample, called the “n”
  • Hypothesis – This is the proposed explanation for the problem discussed in the paper. Not all papers have hypotheses — some authors prefer to use research questions.
  • N – This is the number of respondents in the sample, often reported at the bottom of all statistical tables.
  • Operationalization – The act of defining concepts into measurable variables, allowing concepts to be studied empirically and quantitatively.
  • Qualitative papers – Papers that rely on data that can’t be quantified, like spoken or written word or observations, to examine a particular research question or hypothesis.
  • Quantitative papers – Papers that rely on numbers and statistics to examine a particular research question or hypothesis.
  • Regression – This is a statistical technique that estimates relationships between variables. There are a lot of different types of regressions (linear or logistic are two common ones).
  • Research Question – This is the question that the paper attempts to answer. The answer of the research question is the thesis statement.
  • Significant – This is more precisely called “statistically significant,” and is a statistical indicator that the findings are reliable and likely true, and not due to chance or random variation.
  • Variable, control – This is actually a carry-over from experimental studies, where it was important to try to “control” all outside variation. In statistical studies, control variables are statistically held constant to test the impact of the independent variable on the dependent variable.
  • Variable, dependent – This is the variable that changes based on variations in the independent variable. The dependent variable is dependent on what happens to the independent variable. Some scholars call this the “explanatory” or “outcome” variable to indicate that it is dependent on changes in the independent variable.
  • Variable, independent – This is the variable that causes changes in the dependent variable. Some scholars call these “explanatory variables” because they explain changes in the dependent variable.

Qualitative papers often differ in their set up by nature of the way these papers present data. These papers are often longer than quantitative papers because the data is written and not visually displayed in a table. The section headings may be similar, but the structure of those sections may be different. Qualitative papers rarely have hypotheses, but tend to focus more on research questions. The “data” section will often include details about the researcher’s relationship with the people being studied and their mode of study (interview, content analysis, participant observation are common research methods used in qualitative papers). The findings section will generally be long, due to the nature of the data. For an interview-based paper, for example, the data shown are transcripts of interviews. The findings will involve the transcripts and the analysis of the transcripts. The conclusion/discussion sections are often similar to quantitative papers.