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11 - 20 of 42 results for: SOC

SOC 191: Undergraduate Directed Research

Work on a project of student's choice under supervision of a faculty member. Prior arrangement required.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable 20 times (up to 20 units total)

SOC 192: Undergraduate Research Apprenticeship

Work in an apprentice-like relationship with faculty on an on-going research project. Prior arrangement required.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable 20 times (up to 20 units total)

SOC 193: Undergraduate Teaching Apprenticeship

Prior arrangement required.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable 20 times (up to 20 units total)

SOC 196: Senior Thesis

Work on an honors thesis project under faculty supervision (see description of honors program). Must be arranged early in the year of graduation or before.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable 30 times (up to 30 units total)

SOC 218: Social Movements and Collective Action (SOC 118)

Why social movements arise, who participates in them, the obstacles they face, the tactics they choose, and how to gauge movement success or failure. Theory and empirical research. Application of concepts and methods to social movements such as civil rights, environmental justice, antiglobalization, and anti-war.
Terms: Aut | Units: 4

SOC 224B: Relational Sociology (EDUC 312)

Conversations, social relationships and social networks are the core features of social life. In this course we explore how conversations, relationships, and social networks not only have their own unique and independent characteristics, but how they shape one another and come to characterize many of the settings we enter and live in. As such, students will be introduced to theories and research methodologies concerning social interaction, social relationships, and social networks, as well as descriptions of how these research strands interrelate to form a larger relational sociology that can be employed to characterize a variety of social phenomenon. This course is suitable to advanced undergraduates and doctoral students.
Terms: Aut | Units: 4

SOC 240W: CPI Seminar (SOC 340W)

A workshop devoted to presenting ongoing research on poverty and inequality in the United States. Open to all students interested in (a) building a better infrastructure for monitoring poverty and inequality, (b) building cutting-edge models of the causes and consequences of poverty and inequality, and (b) building better policy to reduce poverty and inequality. Required for all National Poverty Fellows funded by the Stanford Center on Poverty and Inequality.
Terms: Aut, Win, Spr | Units: 1-2
Instructors: Grusky, D. (PI)

SOC 270: Classics of Modern Social Theory (SOC 170)

(Graduate students register for 270). Preference to Sociology majors. Contributions of Marx, Weber, and Durkheim to contemporary sociology. Topics: the problem of social order and the nature of social conflict; capitalism and bureaucracy; the relationship between social structure and politics; the social sources of religion and political ideology; and the evolution of modern societies. Examples from contemporary research illustrate the impact of these traditions. Limited enrollment.
Terms: Aut | Units: 4
Instructors: Red Bird, B. (PI)

SOC 271: Organizational Analysis (EDUC 288)

Principles of organizational behavior and analysis; theories of group and individual behavior; organizational culture; and applications to school organization and design. Case studies.
Terms: Aut | Units: 4

SOC 278: Introduction to Computational Social Science (MS&E 231)

With a vast amount of data now collected on our online and offline actions -- from what we buy, to where we travel, to who we interact with -- we have an unprecedented opportunity to study complex social systems. This opportunity, however, comes with scientific, engineering, and ethical challenges. In this hands-on course, we develop ideas from computer science and statistics to address problems in sociology, economics, political science, and beyond. We cover techniques for collecting and parsing data, methods for large-scale machine learning, and principles for effectively communicating results. To see how these techniques are applied in practice, we discuss recent research findings in a variety of areas. Prerequisites: introductory course in applied statistics, and experience coding in R, Python, or another high-level language.
Terms: Aut | Units: 3
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