141 - 150 of 228 results for: SOC

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.

Through an overview of China's distinctive economic institutions, political system, and growth model, this course provides a framework for understanding the country's remarkable economic advance and rapidly changing prospects. Among the topics covered are China's corporate sector, both state and private, its walled-off financial system, the state's problematic fiscal structure, widening social inequalities, and the global impact of China's economy. The course culminates with an assessment of the country's current economic and political challenges. Same as OSPBEIJ 20. Students may not earn credit for both OSPBEIJ 20 and Sociology 175/275.

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.

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.

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.

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.

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.

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.

CW: SA/GBV. Access the Application Consent Form Here: https://bit.ly/One-in-Five-Application - Over the past decade, the issue of campus sexual assault and harassment has exploded into the public discourse. Multiple studies have reinforced the finding that between 20-25% of college women (and a similar proportion of students identifying as transgender and gender-nonconforming, as well as approximately 10% of male students) experience sexual assault carried out through force or while the victim was incapacitated. This course delves into the complex issues of sexual assault and harassment on college campuses, examining public health, policy, and political dimensions. We explore the prevalence of these issues, the historical and social contexts, and relevant laws such as Title IX and the Clery Act. Through readings spanning health, social science, history, literature, law, and journalism, we analyze responses to campus violence, considering the intersectionality of race, class, gender, and other factors. Guest speakers, including experts and advocates, provide firsthand insights. Sensitive Material: The subject matter of this course is sensitive, and students are expected to treat the material with maturity. Much of the reading and subject matter may be upsetting and/or activating, especially for students who identify as survivors. This course has no therapeutic component, although supportive campus resources are available for those who need them. Elements used in grading: Grades will be based on class attendance, in-person/virtual class participation, and either an independent research paper and class presentation, or a project and class presentation. Enrollment: Requires INSTRUCTOR PERMISSION. Application consent forms are available (https://bit.ly/One-in-Five-Application) or you may contact Professor Burgart at aburgart@stanford.edu and Professor Salles arghavan@stanford.edu. Cross-listed with Feminist, Gender and Sexuality Studies ( FEMGEN 143), Sociology ( SOC 188/288), Anesthesia ( ANES 143). Apply early as demand is high and enrollment is limited to 16 students. Applications will be reviewed on a rolling basis until the class is full.