printer friendly pageSOC 270: Classics of Modern Social Theory (SOC 170)
(Graduate students register for 270). Sociologists seek to understand how society works, specifically: how social life is organized, changed, and maintained. Sociological theory provides hypotheses for explaining social life. All empirical research in sociology is enriched by, and has some basis in, sociological theories. This course introduces students to the earliest sociological theories and the thinkers who developed them. Specifically, we will discuss the work of W.E.B. Du Bois, Emile Durkheim, Max Weber, and Karl Marx. We will compare and contrast how they thought about important modern-day social realities such as capitalism, racism, crime, religion, and social cohesion. We will consider how these early theories and thinkers influence the way sociologists think about and study the social world today.
Terms: Win
| Units: 4
SOC 273: Gender and Higher Education: National and International Perspectives (EDUC 173, EDUC 273, FEMGEN 173, SOC 173)
This course examines the ways in which higher education structures and policies interact with gender, gender identity, and other characteristics in the United States, around the world, and over time. Attention is paid to how changes in those structures and policies relate to access to, experiences in, and outcomes of higher education by gender. Students can expect to gain an understanding of theories and perspectives from the social sciences relevant to an understanding of the role of higher education in relation to structures of gender differentiation and hierarchy. Topics include undergraduate and graduate education; identity and sexuality; gender and science; gender and faculty; and feminist scholarship and pedagogy.
Last offered: Spring 2024
SOC 274: Social Computing (CS 278, SOC 174)
Today we interact with our friends and enemies, our team partners and romantic partners, and our organizations and societies, all through computational systems. How do we design these social computing systems - platforms for social media, online communities, and collaboration - to be effective and responsible? This course covers design patterns for social computing systems and the foundational ideas that underpin them.
Terms: Spr
| Units: 3-4
Instructors:
Bernstein, M. (PI)
;
Baddepudi, A. (TA)
;
Baillargeon, P. (TA)
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Instructors:
Bernstein, M. (PI)
;
Baddepudi, A. (TA)
;
Baillargeon, P. (TA)
;
Escudero, T. (TA)
;
Fuentes, M. (TA)
;
Genc, D. (TA)
;
Hsu, E. (TA)
;
Lee, C. (TA)
;
Suzara, M. (TA)
;
Tran, B. (TA)
SOC 275: Understanding China's Rise (GLOBAL 194, SOC 175)
This course is an overview China's national trajectory since the 1980s, and will place its historic economic advance in comparative perspective. We will examine the factors that made this advance possible, explore the ways that China's political and economic institutions are different from other major economies, and consider challenges that now appear to threaten China's continuing economic advance. Same as
OSPBEIJ 20. Students may not earn credit for both
OSPBEIJ 20 and Sociology 175/275.
Last offered: Winter 2023
SOC 276: The Social Life of Neighborhoods (AFRICAAM 76B, AMSTUD 276, CSRE 176B, SOC 176, URBANST 179)
How do neighborhoods come to be? How and why do they change? What is the role of power, money, race, immigration, segregation, culture, government, and other forces? In this course, students will interrogate these questions using literatures from sociology, geography, and political science, along with archival, observational, interview, and cartographic (GIS) methods. Students will work in small groups to create content (e.g., images, audio, and video) for a self-guided ¿neighborhood tour,¿ which will be added to a mobile app and/or website.
Last offered: Spring 2021
SOC 279A: Crime and Punishment in America (AFRICAAM 179A, AMSTUD 179A, CSRE 179A, SOC 179A)
This course provides a comprehensive introduction to the way crime has been defined and punished in the United States. Recent social movements such as the Movement for Black Lives have drawn attention to the problem of mass incarceration and officer-involved shootings of people of color. These movements have underscored the centrality of the criminal justice system in defining citizenship, race, and democracy in America. How did our country get here? This course provides a social scientific perspective on Americas past and present approach to crime and punishment. Readings and discussions focus on racism in policing, court processing, and incarceration; the social construction of crime and violence; punishment among the privileged; the collateral consequences of punishment in poor communities of color; and normative debates about social justice, racial justice, and reforming the criminal justice system. Students will learn to gather their own knowledge and contribute to normative debates through a field report assignment and an op-ed writing assignment.
Terms: Win
| Units: 4-5
SOC 280A: Foundations of Social Research (SOC 180A)
Formulating a research question, developing hypotheses, probability and non-probability sampling, developing valid and reliable measures, qualitative and quantitative data, choosing research design and data collection methods, challenges of making causal inference, and criteria for evaluating the quality of social research. Emphasis is on how social research is done, rather than application of different methods. Limited enrollment; preference to Sociology and Urban Studies majors, and Sociology coterms.
Terms: Win
| Units: 4
SOC 280B: Introduction to Data Analysis (SOC 180B)
Preference to sociology majors, minors, and co-terms. Methods for analyzing and evaluating quantitative data in sociological research. Students will be taught how to run and interpret multivariate regressions, how to test hypotheses, and how to read and critique published data analyses.
Terms: Aut
| Units: 4
SOC 281: Natural Language Processing in the Social Sciences (PSYCH 290, SYMSYS 195T)
Digital communications (including social media) are the largest data sets of our time, and most of them are text. Social scientists need to be able to digest small and big data sets alike, process them and extract psychological insight. This applied and project-focused course introduces students to a Python codebase developed to facilitate text analysis in the social sciences (see dlatk.wwbp.org -- knowledge of Python is helpful but not required). The goal is to practice these methods in guided tutorials and project-based work so that the students can apply them to their own research contexts and be prepared to write up the results for publication. The course will provide best practices, as well as access to and familiarity with a Linux-based server environment to process text, including the extraction of words and phrases, topics, and psychological dictionaries. We will also practice the use of machine learning based on text data for psychological assessment, and the further statistic
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Digital communications (including social media) are the largest data sets of our time, and most of them are text. Social scientists need to be able to digest small and big data sets alike, process them and extract psychological insight. This applied and project-focused course introduces students to a Python codebase developed to facilitate text analysis in the social sciences (see dlatk.wwbp.org -- knowledge of Python is helpful but not required). The goal is to practice these methods in guided tutorials and project-based work so that the students can apply them to their own research contexts and be prepared to write up the results for publication. The course will provide best practices, as well as access to and familiarity with a Linux-based server environment to process text, including the extraction of words and phrases, topics, and psychological dictionaries. We will also practice the use of machine learning based on text data for psychological assessment, and the further statistical analysis of language variables in R. The course has no computer science prerequisites. Familiarity with Python, SSH, and basic Linux is helpful but not required ¿ they will be minimally introduced in the course, as will SQL (databases) and Jupyter notebooks. Understanding regression, basic familiarity with R, and the ability to wrangle your data into spreadsheet form are expected. For more information, please see
psych290.stanford.edu, where you will be able to access the google form to apply for the class.
Terms: Spr
| Units: 3
Instructors:
Eichstaedt, J. (PI)
;
Lim (Chun Hui), C. (TA)
SOC 287: Ethics, Morality, and Markets (SOC 187)
Markets are inescapably entangled with questions of right and wrong. What counts as a fair price or a fair wage? Should people be able to sell their organs? Do companies have a responsibility to make sure algorithmic decisions don't perpetuate racism and misogyny? Even when market exchange seems coldly rational, it still embodies normative ideas about the right ways to value objects and people and to determine who gets what. In this course, we will study markets as social institutions permeated with moral meaning. We will explore how powerful actors work to institutionalize certain understandings of good and bad; unpack how particular moral visions materially benefit some groups of people more so than others; examine the ways people draw on notions of fairness to justify and contest the market's distribution of resources and opportunities; and consider who has agency to build markets according to different normative ideals. Most course readings are empirical research, so we will also critically discuss how social scientists use data and methods to build evidence about the way the world works.
Last offered: Autumn 2021
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