QUALITATIVE AND MULTI-METHOD RESEARCH SHORT COURSES AT APSA 2019

The QMMR section is sponsoring four short courses at APSA’s annual meeting in Washington D.C.. The courses will be held on Wednesday August 28.

Please see below for the descriptions.

If you have any questions about one or more of the short courses, please contact the instructors listed below.

SC10: Focus Groups: When and How to Use Them (QMMR1) Half Day, 9:00AM – 1:00PM

INSTRUCTOR: Jennifer Cyr, University of Arizona (jmcyr@email.arizona.edu)

Half Day, 9:00AM – 1:00PM

This short course considers focus groups as a data collection method. Its point of departure is twofold: 1. Focus groups help researchers answer certain types of questions, and 2. Focus groups create multiple types of data that help researchers undertake specific and distinct research goals. Having discussed each of these points in detail, we will then explore some of the fundamentals of undertaking focus groups, including the development of a question protocol, the role of the moderator, and how to undertake focus group analysis. Along the way, participants will carry out activities based on actual research.

By the end of the course, participants should be able to identify the kinds of questions that focus groups can help answer and whether they will be useful for their own research design. They should also understand the basics of how to carry out a focus group.

Participants are encouraged to bring specific questions to the course, so we can discuss them as a group. If there is time, the class can examine the research design of different participants and whether focus groups are (or could be) usefully incorporated. In this way, the short course will provide constructive feedback and advice to participants.

SC11: Managing and Sharing Qualitative Data and Qualitative Research Transparency (QMMR2)

INSTRUCTORS: Diana Kapiszewski, Georgetown University (dk784@georgetown.edu), and Sebastian Karcher, Syracuse University (skarcher@maxwell.syr.edu)

Half Day, 9:00AM – 1:00PM

This short course has three central goals. First, the course provides guidance to help scholars manage data through the research lifecycle. We show how participants can meet funders’ data-management requirements and improve their own research by creating a data management plan. We discuss strategies for effectively documenting data throughout the research process to enhance their value to those who generated them and to other scholars. We also provide practical advice on keeping data secure to protect against data loss as well as illicit access to sensitive data. Second, we consider the multiple benefits of sharing data, the various uses of shared data (e.g. for evaluating scholarly products, for secondary analysis, and for pedagogical purposes), the challenges involved in sharing qualitative research data (including copyright and human participants-related concerns), and various ways to address those challenges. Finally, we discuss transparency in qualitative research. Achieving production transparency (i.e., describing how the data drawn on in published work were produced), and analytic transparency (i.e., describing how data were analyzed and how they support empirical claims and inferences in published work) facilitate the effective interpretation and evaluation of scholarly products. We introduce several ways of achieving both types of transparency in qualitative research. We focus in particular on “Annotation for Transparent Inquiry,” a new approach to transparency for work that uses narrative causal analysis supported by individual data sources.

SC14: Process Tracing (QMMR3)

INSTRUCTORS: Andrew Bennett, Georgetown University (bennetta@georgetown.edu) and Tasha Fairfield, London School of Economics (T.A.Fairfield@LSE.ac.uk).

Half Day, 1:30 – 5:30PM

This course will cover the underlying logic and best practices of process tracing, which is a within-case method of developing and testing causal explanations of individual cases.

We will briefly summarize the philosophy of science behind explanation via reference to hypothesized causal mechanisms and then outline the logic of process tracing in terms of Van Evera’s “hoop tests,” “smoking gun tests,” “doubly decisive tests,” and “straw in the wind tests.” We will then explicate an explicitly Bayesian approach to process tracing, which entails asking whether the evidence we find would be more or less plausible if a given hypothesis is true as compared to a rival.

Throughout the session we will emphasize best practices and applications to exemplars of process tracing research. Students will practice applying Bayesian reasoning in small group exercises. As time allows, and depending on the number of students, the instructors will also ask students to discuss how they plan to use process tracing in their current research project. This will allow the instructors and fellow students to offer constructive advice on how best to carry out process tracing in each student’s project.  

SC13: Studying Causal Mechanisms Using In-depth Case Studies (QMMR4)

INSTRUCTOR: Derek Beach, University of Aarhus, Denmark (derek@ps.au.dk)

Half Day, 1:30 – 5:30PM

The study of causal mechanisms is ubiquitous in the social sciences. Mechanism-focused research using in-depth case studies enables us to gain a better understanding of how things work and under what conditions using real-world cases instead of gaining knowledge about mean causal effects across cases based on experimentally manipulating treatments in controlled populations. However, the potential gains of mechanism-focused research have not been fully reaped in the social sciences because of the tendency to reduce mechanisms to counterfactuals, that are then investigated using hypothetical data.  

Inspired by recent developments in mechanism-focused research in medicine and policy evaluation (Clarke et al, 2014; Cartwright and Hardie, 2012), the first session of the course will discuss the standards developed in the natural sciences for what constitutes a ‘good’ mechanistic explanation (Craver and Darden, 2013), and how these can be translated into social science theories. The second session will then present the developing standards in the natural sciences regarding what constitutes ‘good’ mechanistic evidence, and what this can look like in the social sciences. The final session discusses practical applications, including how mechanism-focused research can be used as an adjunct method to improve social science experiments – showing that most good experimental studies already engage in mechanism-focused case studies parallel with their experimental design, but they are just unaware of it when they are theorizing, designing the experiment, and interpreting the data.

Readings:

Beach, Derek, and Rasmus Brun Pedersen. 2019. Process-Tracing Methods: Foundations and Guidelines. 2nd Edition. Ann Arbor: University of Michigan Press.

Cartwright, Nancy and Jeremy Hardie. 2012. Evidence-Based Policy: A Practical Guide to Doing It Better. Oxford: Oxford University Press.

Clarke, B., D. Gillies, Phyllis Illari, Federica Russo, Jon Williamson. 2014. Mechanisms and the Evidence Hierarchy. Topoi, 33(2): 339-360.

Craver, Carl F. and Lindley Darden. 2013. In Search of Mechanisms: Chicago: University of Chicago Press.