printer friendly pageSOC 127: Solving Social Problems with Data (COMM 140X, DATASCI 154, EARTHSYS 153, ECON 163, MS&E 134, POLISCI 154, PUBLPOL 155)
Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use
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Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use real-world datasets to discover meaningful insights for policymakers and communities. This course is the required gateway course for the new major in Data Science & Social Systems. Preference given to Data Science & Social Systems B.A. majors and prospective majors. Course material and presentation will be at an introductory level. Enrollment and participation in one discussion section is required. Sign up for the discussion section will occur on Canvas at the start of the quarter. Prerequisites:
CS106A (required),
DATASCI 112 (recommended as pre or corequisite)
Terms: Aut, Spr
| Units: 5
| UG Reqs: WAY-AQR, WAY-SI
Instructors:
Nobles, M. (PI)
;
Weinstein, J. (PI)
;
Castro Pena, D. (TA)
...
more instructors for SOC 127 »
Instructors:
Nobles, M. (PI)
;
Weinstein, J. (PI)
;
Castro Pena, D. (TA)
;
Charmot, S. (TA)
;
Ma, S. (TA)
;
Ross, D. (TA)
SOC 127D: Gender At Work: Understanding Gender Inequality in the Workplace
Recent events have directed attention to the vastly different workplace experiences individuals encounter based on their gender. But just how does gender structure employment outcomes and experiences? This course will examine the ways in which gender comes to be embedded in organizations and conceptions of work and skill, as well as how gender interacts with other identities, like race, class, and sexuality, to create inequality in the workplace. We will discuss the role of discrimination, bias, and harassment as well as occupational segregation and devaluation in producing unequal outcomes among people of diverse genders. By the end of this course, students will be able to think critically about how gender impacts labor market outcomes as well as develop their own ideas for spaces for further research as well as intervention.
Last offered: Summer 2020
| UG Reqs: WAY-EDP, WAY-SI
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