Module 8: Writing up

Overview

Module 8 brings us full circle: We return to the overall structure of a research report and examine each component in detail. Specifically, we examine the purpose of each component as well as some best-practices for writing each one. In doing so, we examine how these best-practices actually play out in the article on “Judicial Empathy” by Glynn and Sen. The R exercise then invites you to explore and generate some visual tools that we have not yet covered, including interactive plots in HTML.

Objectives

  • Lay out the different components of a social science research report.
    • Explain the purpose of each component as well as some best-practices for writing each one.
  • Explain how Glynn and Sen effectively tackle the different report components in their article on “Judicial Empathy.”
  • Generate a range of visuals for data description, including waffle plots, tree maps, an interactive plots.

Due

  • Thu/Fri @ 8pm. Module 8 Q & A.
  • Fri @ 8pm. Written feedback on report drafts presented during the week. (See my announcement at Canvas, which contains a Workshop Schedule.) Your feedback should be constructive and address substantive and empirical concerns. No length is established, but in general, each draft will merit around 2 pages of single-spaced feedback. Post your feedback to your team page at Ed Discussion.

The Module

Overview and Review of Module 7

As I mention above, this week’s Module brings us full circle in that it re-examines the overall structure of a social science research report, which we first examined in Module 1. This week’s Module builds on Module 1 by examining each component of the research report in detail, laying out the specific purpose of each component as well as some best-practices to keep in mind as you write each one.

Start by watching the video on “Video series overview and Module 7 review.”

Writing up, step by step

Before we dig into the different components of the research report in the video series, you should read the chapter on “The challenge of writing up” by O’Leary and the article on “Judicial empathy” by Glynn and Sen. As you do so, focus on the different components of the research report: What work does each one do?

For the Glynn and Sen article specifically: Try to identify the different components of the research report. Then, try to answer these two fundamental questions:

  • What actually goes into a particular component?
  • What work is a particular component doing?

Here are some of the key components to examine and think about as you read Glynn and Sen. We we examine these as well as a few others in the videos:

  • Introduction
  • Argument and literature review
  • Data and Methods
  • Findings and Discussion
  • Conclusion

Once you have completed the readings and answered the questions above, watch the video series on “Writing up, step by step.” I have divided the series into several smaller components as a means of grouping ideas as well as keeping each video relatively brief.

Title, abstract, and introduction

Literature review and argument

Data description and method (analysis plan)

Findings and discussion

Conclusion and references and Wrap up

Module 8 R exercise on “More plots”

This week’s R exercise invites you to explore and generate some plots that we have not yet covered, including waffle plots, tree maps, and basic interactive plots. Note that for this Module, you should knit your completed RMD to HTML rather than PDF. Download and completed the Module 8 Exercise RMD from Canvas. Complete it and then knit your completed file. You do not need to submit your work.

Module 7: The Literature Review

Overview

Module 7 examines literature reviews: What they are, what they are meant to do, and how we can go about generating them. The Module also explores the importance of surveying existing literature in order to conduct good research more broadly. Indeed, existing literature is fundamental for developing effective questions, arguments, and analysis plans. The weekly R exercise then invites you to reflect on the question of how we can go about visualizing uncertainty and variability in our data analysis.

Objectives

  • Internalize the importance of existing literature for virtually every aspect of research.
  • Lay out the purpose of a literature review and describe the basic process for writing an effective one.
  • Examine two approaches to writing an effective literature review as they crop up in actual research.
  • Use statistical software to visualize uncertainty and variability in your own data.

Due

  • Fri @ 8pm CST: 15-page draft of the research report. See guidelines below. Note that over the weekend, you should read drafts that will be workshopped in Week 8. I will disseminate a workshop schedule toward the end of the week.
  • Thu/Fri @ 8pm CST: Module 7 Q & A

Draft of the research report

Your draft should be roughly 15 pages. It should be double-spaced and use 12-point Serif font. Your draft should lay out (1) your research question and its motivation; (2) a brief literature review; (3) your argument; (4) your data and analysis plan with justification; and (5) two plots, tables, or other visualization that motivate your question and/or support your argument.

Your draft should be complete and demonstrate thought and effort. That is, whereas this is meant to be a draft that you will revise and augment between now and the end of the quarter, it should nevertheless reflect that you have been thinking about and refining your question, argument, analysis, and grasp of the relevant literature during these past 7 weeks. In addition, your draft should not come across as having been hastily written; you should therefore revise your draft for clarity, precision, and concision before submitting it.

The Module

Review of Module 6

Module 7 focuses on the literature review. As with previous Modules, however, it begins with an overview of the Module videos as well as a very brief review of Module 6 on “Analysis Plans”. Watch the video on “Module 6 Review.”

Uses of Literature

The next video examines the role played by existing literature in different components of research. We have of course already examined this idea to a degree. For instance, in our discussion of research questions, we underscored the importance of surveying prior studies for generating and refining our questions. The video builds on this intuition by examining how we should be incorporating prior work at different points in the research process.

Watch the video on “Uses of Literature.”

The Literature Review

The next video is the real meat of the Module in that it lays out the literature review: What it is, what it is meant to do, and how we can go about writing one effectively. We also examine two different approaches to writing a literature review and what these approaches look like in actual scholarship. Toward this end, you should start by reading the articles by Schillbach on “Alcohol and Self Control” and Kocher et al. on “Rabbit in the Hat.”

Both of these articles are fascinating, so you should read them in their entirety. But, given this week’s topic, you should focus on how the authors engage existing literature on their topic in order to build their own arguments. Accordingly, here are some questions that you should try to answer as you read:

  • What is the focal relationship in each piece (i.e., What is the main IV and DV)?
  • How do the authors organize their engagement of the literature? Do they seem to focus on literature surrounding their IV, or their DV?
  • How do the authors group different citations? Why do you think that they grouped them in the way that they did?
  • Find one or two citations in each piece. What does the citation do for the author? What point does it help them make?

Now read Schillbach and Kocher et al. Once you have finished reading, watch the video on “The Literature Review.”

Zotero

I should note that Zotero is an excellent resource for organizing citations and generating bibliographies. If you have not used Zotero before, I highly recommend it. A very brief introduction to using Zotero is available at the UC Library website: https://guides.lib.uchicago.edu/c.php?g=297676&p=1986555

R Exercise on Depicting Uncertainty

This week’s R exercise asks you to reflect on uncertainty: How to think about it, and how to report it visually. You will work with your own data to generate some tables and plots that aim to capture uncertainty and variability in your data. You are likely to include some of these in your final research report, so I highly encourage everyone to complete the exercise in R or Stata.

First read the very brief article by Hullman on “Confronting Unknowns.” Once you have read, proceed to the Module 7 R Exercise, which is available for download at Canvas. If you are using Stata, I have copy-pasted a portion of the Exercise instructions below:

—–

The Module 7 RMD invites you to reflect on uncertainty: How to think about it, and how to capture it visually. I have therefore asked you to begin by reading Hullman’s brief article on “Confronting Unknowns.”

Critically, we often confuse uncertainty and variability. Uncertainty means that we do not know a particular quantity. For instance, we we may not know with precision the proportion of voters that will vote Democrat in an upcoming election. By contrast, variability means that a particular variable can take on a range of different values. For instance, each time we conduct a survey, a different proportion of respondents will state that they plan to vote Democrat in an upcoming election.

As with last week’s RMD, you will work with your own data. Start by cleaning your data as necessary. Then proceed below.

In this section, use your own data to create a plot or other graphic that depicts some quantity of interest AND the uncertainty OR variability around it. For example, your quantity of interest could be something along the lines of:

  • Average life expectancy across sub-Saharan Africa.
  • Average perceived level of inequality across countries.
  • Average decrease in enrollment across colleges and universities under Covid-19.
  • Proportion of Divvy users who own annual memberships (or month-to-month memberships).
  • Average decrease in expected educational achievement for each additional child added to a family.

You can choose from a wide range of ways for visually depicting these quantities. Here are some of these ways. Note that whereas I have included some potentially useful resources for generating these graphs in R, Stata users may need to use an internet search in order to find comparable resources:

Module 3: Theory, hypotheses, and arguments

Overview

Module 3 builds on Module 2 by examining theory, hypotheses, and arguments. We distinguish between these concepts but also reflect on how they work together within a final research report: In particular, we focus on the linkage between theory (our answer / logic) and hypotheses (the empirical implications of our theory). We examine some common pitfalls that crop up whenever we find ourselves working with imperfect data as well as some strategies for avoiding them.

Objectives

  • Differentiate theory, hypotheses, and arguments.
    • Explain how these concepts work together within a research report.
  • Identify common pitfalls in linking theory and hypotheses and explain how we can avoid them.
  • Analyze the linkage between theory and evidence as it crops up in Lessing and Willis.
  • Recall and practice the basics of cleaning and transforming data using dplyr.
  • Reflect on how to give substantive and constructive peer feedback during the week’s team meeting.

Due

Mon. @ 8pm CST. Write 1-2 paragraphs of feedback on each of your team members’ initial research designs. Post your comments as an attachment beneath your team’s sub-heading at Ed Discussion. If you are the first member of your team to post, please create a new thread.
Thu. / Fri. @ 8pm CST. Post your Q & A about the week’s reading at Ed Discussion.

Theory, hypotheses, and arguments

Before diving into the week’s concepts, let’s briefly review some of the concepts that we examined in Module 2 on “Research areas, topics, and questions.” Toward that end, watch the video on “Recap of Module 2.”

Now that we have examined research questions, let’s turn our attention to theories, hypotheses, and arguments. Before you watch the videos below on this topic, read the Chapter by Bryans et al. on “Explaining the Social World.” As your read, think about your answers to the following questions. Doing so will prepare you to better engage the video content and, hopefully, assist you as your progress in your research:

  • What is theory? What are hypotheses? How do these concepts go hand-in-hand?
    • Think about your own research proposal: Did it have a theory (or just hypotheses)? What is your theory?
  • How did you develop your theory? Did you mainly use induction or deduction?
  • What assumptions do you make in your theory?
    *If your theory is correct, what do expect to observe in the world? In other words, what is the best evidence you could find that would tell you that your theory is correct?

Now watch the videos on “Theory, hypotheses, and arguments” and “Why theory?”

The next video aims to get you thinking critically about how we can effectively link theory to hypotheses: “If your theory is correct, what should we observe in the world?” Doing this well is not easy, in part because we rarely find perfect evidence in support of our theories.  When this happens, it’s easy to step into some common pitfalls rather than take the more appropriate step of gathering additional evidence or modifying our theory to ensure it is useful despite empirical limitations. The next video examines some of these common pitfalls as well as some strategies for avoiding them. Be prepared to pause the video throughout, as this video is meant to be a sort of exercise in “spotting the fallacy.”

You will now read “Legitimacy in Criminal Governance” by Lessing and Willis. I selected the article not only because it is one of the most interesting academic articles you will ever read but also because it exemplifies the meme that I presented in the video on “Why theory?” above. That is, Lessing and Willis help us to interpret/connect/make sense of some rich data that I think are extremely puzzling.

Before you read, think about your intuitions to the following questions:

  • How do you think criminal organizations (e.g., mafias and drug gangs) keep their members in line?
  • If your answer (theory) is correct, what would you expect to find if you could examine the internal working of one of these criminal organizations?

Now read the article. When you have finished, watch the video on “Anatomy of an argument.”

R exercise on tidy data and dplyr review

If you are completing the R exercises each week, be sure to download the exercise for Module 3 from Canvas. This week’s exercise is meant to help you brush up on your data cleaning and transforming skills using the dplyr package. While this is less fun than the webscraping we did last week, it is probably more useful, as most of you will have to spend some time cleaning, transforming, and merging any data that you obtain for use in your final research report.

Module 2: Research areas, topics, and questions

Overview

Module 2 examines research questions: in particular, the attributes of a good research question, and a general process we can follow to move from a broad research area to a more specific topic and, finally, a focused question. The module will ask you to reflect

Objectives

  • Grasp the attributes of a good research question
  • Grasp the process for developing a good research question and begin to implement it
  • Examine the development of a research question by engaging a real-world example
  • Examine and practice web scraping in R

Due this week

  • Thu and Fri @ 8pm CST: Ed discussion Q & A.
  • Fri @ 8pm CST: Proposed research design. Submit via the Assignments section at Canvas. Also post as an attachment beneath your team’s heading at Ed Discussion. NOTE: You should read each others’ proposals and prepare 1-2 paragraphs of feedback for each one. You will be required to post your written feedback to Ed Discussion by Mon. 4/12 @ 8pm (Week 3).

Some guidance on research designs

Your proposed research design should be a roughly 1-page, single-spaced document. It should do three things: (1) lay out a research question and justify it; (2) delineate a brief answer to the question; and (3) discuss the sort of data you will need in order to answer the question and why.

The readings and videos for this week are meant to help you to develop your research question and design. So, if you can, try to complete the reading and watch the videos relatively early in the week.

I want to preview a couple of key points from the reading and videos here as means of reassuring and guiding you. In particular:

  • Your research question and design will evolve. In fact, it will likely continue to evolve even as you conduct your analysis and write up your results toward the end of the quarter. (I am still constantly revising the design document for my own dissertation as it becomes a book!) This can be frustrating, but it is inevitable. You will be moving in and out of the literature and data surrounding your question in upcoming weeks, and in doing so, you will get a much better idea about what makes a “good” question as well as the sorts of questions you can examine given the available data.
  • For part 3, it is not necessary that you have specific data / datasets in mind. You can instead approach this as a thought experiment: Given your question and tentative answer, what are your ideal data and why? What sort of measures would you obtain? What would the units of analysis be? Would the data be cross-sectional, panel / time-series, or something else? Are the data likely to derive from an experiment, survey, or machine-learning algorithm, or are they likely to have been hand-coded by scholars? The more you think through these and related questions, the better. Thinking carefully about your ideal data now will help you to identify workable data later.

The Module

Attributes of good questions and developing your question

First read the chapter on “Beginning the research process” by Buttolph Johnson. As you read, think about your answers to the following questions. You don’t need to write your answers down, but thinking about them will help you to develop your own research question:

  • What are some attributes of a good research question?
  • How does one actually go about developing a good research question?
  • How does the literature review go hand in hand with the development of a good question?

Once you have completed the Buttolph Johnson chapter, watch the three videos below on “Research areas, topics, and questions”. Note that you will need to enlarge the videos in order to view them.

Anatomy of a research question

Now read the article by Albertus and Deming on “Branching out.” You should read the entire article. In your reading, you might try to implement some of the advice laid out by Dane’s chapter on “Reading and structuring research” in Module 1. In addition, in line with this week’s overarching topic, here are some questions to think about as you read. To the degree that there is time, we may discuss some of these questions during our team meetings this week:

  • What is the central question that the authors ask?
  • What have other scholars found in terms of answers to this question (or very similar questions)?
  • Given that the question is not really new, what contribution – if any – do you think that the authors make?
  • What sort of data would you want – in theory – in order to answer the question posed by the authors?
  • What data do the authors actually use and how does it differ from the ideal data that you described above?
  • How do the authors justify the data that they use?

Once you have read the article, watch the video on “Anatomy of a research question.”

R exercise on web scraping

Remember that you are not required to complete and submit the weekly R exercise for a grade. They are a voluntary tool for introducing you to some operations in R that you may find useful this quarter and/or in the future. This week’s exercise introduces you to one procedure for scraping data from the web pages written using HTML. I am not an expert on this topic, so any data scientists with experience in web scraping should feel free to post additional resources and advice at Ed Discussion.

Note that for this exercise, you will need to add SelectorGadget to your web browser. I use Chrome and have installed the SelectorGadget extension from Chrome’s Web Store (https://tinyurl.com/298y44yt). For other browsers, you can simply drag the SelectorGadget bookmarklet to your bookmarks toolbar. You can find the bookmarklet at selectorgadget.com.

I have included a very brief video below that introduces the selector tool as it applies to this week’s R exercise.

Module 1: Reading and structuring research

Overview

Module 1 begins by walking through the course Syllabus. It then kicks off our examination of the different components of good research design by laying out strategies for critically reading and structuring a quantitative social science research report. It then asks you to critically examine a summary report by the Chicago Million Dollar Blocks Project as well as use the Project’s data to create a basic plot using GGplot.

Objectives

  • Logisitics
    • Examine the course Syllabus
    • Enroll in weekly team meeting via email
  • Reflect on strategies for critically reading quantitative social science research
  • Describe the main components of a social science research report, their contents, and their purpose
  • Reflect on the linkage between theoretical claims and data analysis via examination of the Chicago Million Dollar Blocks Project.

Due

  • You should send an email to me with 3 times that you are available to regularly meet with a team of 3-5 students. See the Syllabus for details and available times. Email me by Thursday evening.
  • Ed Discussion Q&A are due at 8pm CST on Thursday (Q) and Friday (A) each week. This week, you only need to post one comment by Friday at 8pm. Your comment should center on the Chicago Million Dollar Blocks Project. See below.
  • The Module 1 exercise is due at 8pm CST on Friday.

Module 1

Syllabus

Watch the video on “Course Syllabus.” If you have questions about the Syllabus after watching the video, please post your question to Ed Discussion under “Course logistics” so that other students can view the answer.

Course Intro.

Course format

Assignments and grading

Final research report

Course policies

Course schedule

Reading and structuring research

How to read and structure research may seem relatively straightforward; it may even seem obvious. You are at Chicago, after all, in part because you are a good reader. You are also probably a decent writer and have some good intuition about how to do research. But quantitative social science research can be a strange form. It is thus critical that we become deeply familiar with the form — its structure, conventions, jargon, and so forth — so that we can read it critically and, ultimately, apply it to our own research. With this in mind, I encourage you to reflect on your answers to the following questions as you read the Dane and Buttolph Johnson chapters:

  • How does critical reading of quantitative research differ from reading, say, an ethnographic study?
  • What are the different components of a quantitative research report?
  • And more critically perhaps: What should each component do? What is its contribution to the report as a whole?

Now read “Reading a research report” by Dane and “The research report: An annotated example” by Buttolph Johnson.

The Chicago Million Dollar Blocks Project

In addition to examining and reflecting on the different components of quantitative social science research, we are going to examine lots of data and data visualizations this quarter. We will do so mainly via readings, brief videos, and weekly exercises in R. The aim here is to get you thinking about how to effectively support a theoretical using good data and and detailed data analysis.

Go to the Chicago Million Dollar Blocks Project (https://chicagosmilliondollarblocks.com/). Carefully read the web page and examine the data presented there.

The Project begins to exemplify what you will do this quarter: In particular, it uses high-quality data to support a claim about a high-interest and pressing social topic. But there are also areas in which the “report” shown at the Project’s web page could be improved. In this vein, think about your answers to the following questions as you study the page:

  • What is the aim of the web page? What is it trying to do exactly?
  • What is a “war on neighborhoods”?
  • What evidence exists of a war on neighborhoods?
  • What sort of statistic would be clear and compelling evidence in support of the Project’s main claim (as you understand it)?
  • Are you persuaded? If not, how might you improve the web page to make it more compelling?

For this week’s Q&A, post one way that you might try to improve the “report” shown at the Project’s web page. Post your comment to the thread that I have created at Ed Discussion by Friday evening at 8pm CST. The thread is under “Reading Q&A / Chicago Million Dollar Blocks Project.” You are not required to post an additional reply this week, but you may do so if you wish.

Once you have scrutinized the Project web page and posted at Ed Discussion, complete the Module 1 exercise, which uses data from the Chicago Million Dollar Blocks Project. Download the exercise from the “Module 1” folder located at the “Files/Module 1” section of Canvas. Also download the corresponding dataset. Complete the RMD file, render it to PDF, and upload your PDF to the “Assignments” section of Canvas.