Wednesday 2:30pm-5:15pm

Tarbutton Hall 206

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 presentations and discussions of their research projects. 

This course's primary goal is for students to gain fluency in the foundational statistical methods in the social sciences. Fluency denotes the ability to 1) assess the methods' appropriateness to address sociological questions, 2) provide thoughtful reviews to works using these methods, and 3) actively engage in collaborations that use statistical methods. This course aims to provide a broad survey of the most commonly used generalized linear models rather than expert knowledge in any particular approach; each topic is worthy of its own semester-long course.

The success of this course depends critically on active participation. As such, students will be evaluated on their intellectual engagement during class discussions and presentations. Please complete the assigned readings before class. This course also requires students to complete an extended abstract or a preliminary analysis of an empirical paper. The final project will be evaluated on its transparency and reproducibility rather than its methodological sophistication.  Stage assignments throughout the semester will allow for opportunities for feedback and revision. 

Lastly, the primary focus of this course is not statistical programming. I do not expect you to memorize the commands and options for all the statistical methods that we will cover in this course. Instead, I expect you to understand the theory and assumptions behind the methods so that you will be able to figure out the programming part in the future. We will still heavily rely on software for analysis and documentation throughout the course. I will provide support for Stata and R. 

Learning Objectives

1. Gain fluency in the application of generalized linear models in social science research
2. Adopt practices for transparent and reproducible research
3. Practice thoughtful feedback and collaboration in a working group setting
4. Complete an extended abstract of an empirical article

Required textbook and readings

ISBN: 9780520296954 Christensen, G., J. Freese and E. Miguel. 2019. Transparent and Reproducible Social Science Research: How to Do Open Science: University of California Press.

ISBN: 9780520289291 Hoffmann, J.P. 2016. Regression Models for Categorical, Count, and Related Variables: An Applied Approach: University of California Press.

ISBN: 978-0761916727 Allison, P. D. 2002. Missing data. SAGE Publications, Inc.

Tuesday 1:00pm-3:45pm

Tarbutton Hall 206

Course Description:

This workshop focuses on teaching sociology grad students how to produce research, ranging from the initial design of a study to eventual submission for publication. The following types of sociology graduate students will be eligible for participation in the workshop: (a) those who specialize in culture and/or social psychology; and (b) those who are currently involved in some stage of the research process beyond the second-year paper requirement (e.g., beginning a project, revising a paper, submitting a grant proposal, conducting data analysis, working on a dissertation proposal). Throughout the semester, we will address the particular efforts of each student.  Each workshop member will provide constructive comments at our meetings. 

Monday/Wednesday 1:00pm-2:15pm

Tarbutton Hall 106

Course Description:

The course deals with new tools of data analysis and visualization, especially for text data (Natural Language Processing, NLP). It is a very demanding 4-credits course, fulfilling the writing requirement since it requires extensive weekly writing.

The course relies on the Stanford parser CoreNLP as the main NLP engine, but a number of other NLP tools will also be used: topic modeling with Mallet and Stanford Topic Modeling Toolbox, Word2Vec, vectors representations of words, shown to capture many linguistic regularities of a corpus, N-grams and word co-occurrences viewers, sentiment analysis. Through these tools, the course will show how to analyze small/large corpora of text. While we have a series of tools (in Java and Python) that can be run from command line, students would greatly benefit to use the freeware software PC-ACE. The software runs under Windows only. Mac users will have to install Windows and MS ACCESS (both free for Emory students) on their machines via Virtualbox (free for Emory students).

The course will also show how to use different tools of data visualization, especially network graphs dealing with relationships between objects (social actors, concepts, or just words), both static and dynamic (changing with time), and spatial maps dealing with objects in space (and time, dynamic maps) through Geographic Information System (GIS) tools. We will focus on freeware software, from Gephi to Cytoscape, Palladio, Google Earth Pro, QGIS, Carto, TimeMapper.

Students are required to come to the class with a corpus of textual data (e,g,, newspaper articles, books, blogs, websites) that they wish to analyze.

Thursday 2:30pm-5:15pm

Tarbutton Hall 206

Course Description:

This is a graduate level theory course designed to examine the social, institutional, political,

cultural and ideological contents of modernity, and its discontents. We will approach our inquiry

through the intellectual framework of racial colonial capitalism.

My learning objectives for you in this course are four-fold. I want you to: 1) further develop a

disciplined practice of close reading—a practice that is crucial to the work of a social theorist, 2)

enhance your level of theoretical sophistication (which comes from being well read in your field,

and others), 3) put into practice the art of asking beautiful questions (don’t you just abhor those

long non-question questions that folks ask at conferences? Me too! Asking profound, thought

provoking, expansive-yet-concise questions actually comes from intentioned practice), and to 4)

walk away with a more historically-based and nuanced understanding about race, racism and

processes of racialization.

Tuesday 4:00pm-6:45pm

Tarbutton Hall 206

Course Description:

In this course we investigate the question, “What is the relationship between technology and inequality?” We do so in three ways. First, we explore debates among sociologists, economists, and communication scholars about the extent to which technological change has contributed to various forms of inequality (e.g., education, wealth, health) and how this intersects with inequalities by race, class, and gender. Second, we explore theoretical tools and vocabulary, including what scholars call the first-, second-, and third-level digital divides. First-level divides concern issues of access to technological resources. Second-level divides focus on differences in technological skills and literacies. Third level divides emphasize the relationship between skills and literacies and broader social inequalities. We examine scholarship on each of these divides, what it shows about the relationship between technological change and inequality, and also investigate critical issues beyond the framework of the digital divide, like algorithmic bias. As we investigate these topics, we will attend to the theoretical, substantive, methodological, and political considerations that concern the study of digital inequality. Finally, students will engage in research in digital inequality: manuscript review and a course project (e.g., an individual or collaborative research paper on an ongoing project, a proposal for future research, or a public sociology project, depending on what would best support students’ future work).

Books

ISBN: 978-0226732695 Puckett, Cassidy. Redefining Geek. University of Chicago Press

First edition

Tuesday 1:00pm- 3:45pm

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. Irene Browne (our Director of Graduate Studies) about enrollment.

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

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

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

Read more about these credits here.

Monday 6:00pm-8:45pm

Tarbutton Hall 206

Course Description:

This course discusses "theorizing"--how to think theoretically and how to come up with good theoretical ideas. It includes a review of major epistemologies in social science and a step-by-step practice of theorizing. 

Books: 

ISBN: 978-0333774991 Benton, Ted, and Ian Craib. 2011. Philosophy of Social Science. Basingstoke: Palgrave Macmillan. 

ISBN: 978-0335208845 Gerard Delanty, Piet Strydom. Philosophies of Social Science: The Classic and Contemporary Readings. Open University Press.  

ISBN: 978-691155227 Swedberg, Richard. 2014. The Art of Social Theory. Princeton: Princeton University Press. 

ISBN: 978-0393978148 Abbott, Andrew Delano. 2004. Methods of discovery: heuristics for the social sciences, Contemporary societies. New York: W.W. Norton & Co. 

Wednesday 8:30am- 11:15am

Tarbutton Hall 206

Course Description:

This course is organized as a practical workshop. Class sessions will involve a combination of hands-on activities, discussions, guest “presentations” and practice teaching sessions. We will approach teaching as a collective endeavor; students will be responsible for: leading discussion of the readings and topics; providing feedback on each other’s course materials; preparing for each other’s practice-teaching session and sharing information and experiences about teaching. Throughout the course, we will cultivate our individual pedagogical approaches and modes of teaching, linking these themes to practical nuts and bolts of teaching. Flexibility is built into the syllabus—we may adapt the syllabus to accommodate your specific interests, needs and goals as they emerge. By the end of the class, you will have created a syllabus and supporting materials (assignments, exams, projects, etc.)  for an undergraduate sociology course.