Thursday 2:3-5:30pm

Tarbutton Hall 206

Course Description:

In this course, we will investigate what it means to utilize qualitative methods in social science research. To do so, we will 1) examine the epistemological underpinnings of qualitative research; 2) consider issues such as subjectivity, ethics, validity, rigor, and causality; 3) practice various qualitative data collection and analysis methods; and 4) discuss practical issues such as framing and operationalizing research questions, designing feasible projects, selecting samples, managing data collection and analysis, presenting and publishing findings, and pursuing funding for qualitative research. The goal of the course is for students to develop the skills, techniques, and knowledge necessary to design and undertake independent qualitative research (or mixed methods research)—or to be conversant in qualitative methods to engage with qualitative scholarship in the social sciences. The final outcome of the course is that students walk away with an initial experience in qualitative research methods as well as a draft of a grant proposal for the National Science Foundation or other equivalent that uses qualitative or mixed methods.

The course begins with present-day and past debates about how to best conduct qualitative research—and its place in the social sciences. We then move into an overview of qualitative methods and “doing” qualitative research. We will explore research design issues including developing research questions and selecting samples. We will then examine the collection, analysis, and presentation of qualitative data, using exercises and your own research projects to illustrate these processes—including observations, interviews, and content analysis. We will be concerned with practical issues that arise during the research process. We will close with a discussion of major issues in qualitative research including subjectivity, ethics, IRB, causality, validity, rigor, as well as touch upon how to conduct mixed-methods research.

Tuesday 2:30-5:30pm

Callaway S107

Course Description:

This course builds upon the statistical toolkit from SOC 500 Linear Regressions and provides a foundation for conducting and evaluating regression-based works in the social sciences. The first part of the course will cover the topics in conducting transparent and reproducible research. Students will be expected to adopt these research practices throughout the semester. The second part of the course will cover generalized linear models (GLM) that examine non-linear outcome variables. The readings, lectures, and in-class discussion will address each method's mathematical justification, execution, and interpretation using statistical software and application in published articles. The third component of the course will focus on students' in-class presentation and discussion of their research projects. The primary goal of this course is for students to gain fluency in the foundational statistical methods in the social sciences. Fluency denotes the ability to 1) to assess the methods' appropriateness to address sociological questions, 2) to provide thoughtful reviews to works using these methods, and 3) to actively engage in collaborations that use statistical methods. This course aims to provide a broad survey of the most commonly used generalized linear models.

Required Texts:

1) ISBN: 978-0520296954 Christensen, G., J. Freese and E. Miguel. 2019. Transparent and Reproducible Social Science Research: How to Do Open Science: University of California Press. 

2) ISBN: 978-0520289291 Hoffmann, J.P. 2016. Regression Models for Categorical, Count, and Related Variables: An Applied Approach: University of California Press. 

3) ISBN: 978-1597180474 Long, J. Scott. 2009. The Workflow of Data Analysis Using Stata: Stata Press. 

4) ISBN: 9781597181112 Long, J.S., J. Freese and StataCorp LP. 2006. Regression Models for Categorical Dependent Variables Using Stata, Second Edition: Taylor & Francis.

5) ISBN: 978-1498715379 Gandrud, C. 2016. Reproducible Research with R and R Studio: CRC Press. 

Monday/Wednesday 2:30-3:45pm

Emerson Chemistry Building E-101 (16)

Course Description:

Interest in network analysis has EXPLODED in the past few years, partly due to the latest advancements in statistical modeling and the rapid availability of network data and partly due to the recognition that many analytical problems can be re-cast as a network problem. Aiming to examine social connections and interactions quantitatively, network analysis has become an essential method and tool for studying a variety of issues in social and natural sciences. This course covers the major methods to collect, represent, and analyze network data. Selected topics include centrality analysis, positional analysis, clustering analysis, the exponential random graph model for modeling network formations, the stochastic actor-oriented model for dynamic network analysis, meta network analysis, weighted network analysis, text network analysis, causal analysis of network effects, and social network-based predictions and interventions. Examples are drawn from a wide range of disciplines including business, economics, education, political science, public health, and sociology. Students will learn hands-on skills to conduct their own research by using mainstream network packages in R such as “statnet” and “RSiena”. This course requires a basic knowledge of logistic regression and basic programming skills in R.

Recommended (Not Required) Textbooks:

1. Wasserman, Stanley and Katherine L. Faust. 1994. Social Network Analysis: Methods and Applications. New York: Cambridge University Press. (ISBN- 978-0521387071)

2. Lusher, D., Koskinen, J. & Robins, G. 2013. Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications. Cambridge University Press. (ISBN- 978-0521141383

Wednesday 4:00-6:45pm

Emerson E-102

Course Description:

For years we have understood that race is, biologically speaking, an exceedingly complex matter and that preconceived biases much more than biology govern the way people think about race. In this course, we do away with a singular notion of race, ethnicity, and racism and embrace the colonialist, imperialist function of the terminologies in both the U.S. and abroad. This course highlights key theoretical, methodological, and empirical readings in the sociology of race, ethnicity, and nation. We enter as equal partners into important, ongoing debates surrounding the relationship of race, ethnicity, and nation to each other and to society. We will discuss the biological myth, the social reality, and the structural construction of race and ethnicity. In particular, we will focus on the social significance of race by examining the reality of ethnoracial stratification, the reality of the experience of race, and the rationality of those who study ethnoracial dynamics and processes. During this course you will learn the origins of the concept race, explore the historical science and statistics used to justify racial thinking, clearly distinguish among dominant sociological theories of race and ethnicity, and review several empirical works on race in Sociology. As an end product, you will produce a term paper that engages an important debate within the field of race, ethnicity, and nation through critical review and/or analytical inference.

Required Readers/Textbooks:

1. Beck, Les and John Solomos (2001). Theories of Race and Racism: A Reader. New York: Reader. ISBN: 978-0415412544
2. Golash-Boza, Tanya. 2017. Race and Racisms: A Critical Approach. New York: Oxford University Press. Second Edition. (ISBN: 9780190663780)
3. Ray, Rashawn. 2010. Race and Ethnic Relations in the 21^st Century: History, Theory, Institutions, and Policy. San Diego, CA: University Readers. (ISBN: 9781935551607)

Tuesday 9:00am-12pm

Tarbutton Hall 206

Course Description:

This course will provide masters and doctoral level students with an interdisciplinary survey of research and writing on the public health implications of religious practices, beliefs, and institutions.  The course will emphasize evidence from quantitative social science and epidemiology and the role of religion in the historical development of public health institutions to identify religion’s role as a social determinant of health.

Required Tex:t

1. ISBN: 9780199362219: Religion as a Social Determinant of Public Health, Ellen Idler, Editor. 2014. (New York: Oxford University Press)  

Tuesday 2:30-5:30pm

Tarbutton Hall 206

Course Description:

The primary goal of this seminar is to facilitate the completion of the second-year research paper requirement. Towards that end, the seminar instructs students regarding conceptual and pragmatic issues associated with empirical research. Assignments pertaining to students' own empirical research projects will complement dialogue about such issues to ensure progress on students' projects.

These offer credit for individualized work with a given faculty member.

Please consult with your advisor and / or Dr. Ellen Idler (our Director of Graduate Studies) about enrollment.

These offer credit for ongoing research overseen by a given faculty member.

Please consult with your advisor and / or Dr. Ellen Idler (our Director of Graduate Studies) about enrollment.

These offer credit for participation in assistantships (TATT 605C) and for teaching one's own class (TATT 610SOC).

Read more about these credits here.