I have a 10-hour Graduate Research Assistant position available in 2021 spring (for UT students only). The project will examine bias and social stereotypes in the nonprofit sector using computational methods. Publication and authorship are possible depending on contribution. The successful applicant is expected to have the following qualifications:
- Use Python as a primary coding language.
- Familiar with web crawling and markup languages (e.g., XML and HTML).
- Proficient in natural language processing, contextual word embedding (e.g., BERT) in particular.
- Know how to examine and process bias in word embeddings (e.g., https://arxiv.org/abs/1607.06520 ).
- Knowledge in sociology or psychology is a plus.
Please send your 1) CV, 2) a letter stating your qualifications (300 words max), 3) source codes of your project meeting the qualifications, to firstname.lastname@example.org.
Application deadline: 2021-01-10
The visit is canceled because of COVID-19. We will update you if we have further information.
Please save the date for Dr. Ronald Burt’s visit and lunch talk at UT Austin. He will be available to meet students (9:30-11am) and faculty (2:30-3:30pm). Please RSVP here.
- Lunch talk topic: Trust and cooperation beyond the network
- Time: 4/9/2020, 12:00-13:30
- Lunch talk location: Bass Lecture Hall at the LBJ School
- Abstract: This work has two goals: explore the research strategy of combining incentivized game behavior with large area probability surveys, and use the research strategy to explore how the network structure around a person predicts trust and cooperation beyond the network. Reasoning from research within networks, we hypothesize that network closure has a negative effect on trust and cooperation beyond the network. We find empirical support for the hypothesis in game play and network data on a large area probability sample of Chinese CEOs. More, success is the tonic that animates the hypothesis. Trust and cooperation from CEOs running less successful businesses is independent of their network. In contrast, successful CEOs with closed networks are particularly likely to defect against people beyond their network, and successful CEOs with open networks are particularly likely to cooperate beyond their network. We demonstrate the robustness of our empirical evidence, and discuss future use of incentivized games to obtain behavioral data from respondents in large area probability surveys.
“Ronald Stuart Burt is an American sociologist and the Hobart W. Williams Professor of Sociology and Strategy at the University of Chicago Booth School of Business. He is most notable for his research and writing on social networks and social capital, particularly the concept of structural holes in a social network.” (Wikipedia introduction)
This is a Data Science Speaker Series event and sponsored by the RGK Center for Philanthropy and Community Service and Research Design Working Group.
Wed Nov 20, 2019 9-12am, RLP 1.404 Computer Lab
This workshop will introduce the use of the China Biographical Database (CBDB), mapping data using GIS, and graphing social networks. CBDB is a relational database of 427,000 men and women, mainly from the 6th through 19th centuries. Participants will be given a copy of the complete database.
Peter K. Bol
Professor Peter K. Bol is the Charles H. Carswell Professor of East Asian Languages and Civilizations at Harvard University. He was also the Vice Provost for Advances in Learning between 2013 and 2018.
CBDB Project Manager at Harvard University
We will solve real-world civic issues by analyzing open government data and building computer programs or models. You can assemble a team with students from or outside of the class. Your team can choose from the following problems:
Eligibility and requirements:
- Course students are required.
- All current UT Austin full time graduate (9 credit hours) or undergraduate (12 credit hours) students are eligible, but need to apply. The selection process is competitive.
- Need to work as a team with 2-4 people.
- First Prize Group: $500
- Second Prize Group: $300
- Third Prize Group: $100
Depending on the University’s operating procedures, final rewards may be distributed as cash or credits for student loan or course.
- October 1st – 14th: Outreach, receiving applications.
- October 15th – 31st: Team preparation and working with domain experts.
- November 2nd: Hackathon day.
- 10am-12pm: Team work and feedback from domain experts.
- 12pm-1:30pm: Break.
- 1:30pm-4pm: Finalize work and presentation.
- 4pm-5:30pm: Team presentations.
- 5:30pm-6pm: Announcing awards.
- Outstanding deliverables.
- Efficient team work.
- Well-organized presentation.
- Evidence of learning while completing the task.
- Bixler, Patrick, PhD, Assistant Professor of Practice at the RGK Center and LBJ School of Public Affairs.
- Ma, Ji, PhD, Assistant Professor at the RGK Center and LBJ School of Public Affairs.
- Rudow, Josh, PhD, Senior Planner, City of Austin.
- Taylor, Reyda, PhD, Senior Consultant, Data & Evaluation, Mission Capital.
The final project is supported by UT Austin Graduate School’s Academic Enrichment Fund and RGK Center Special Funds for Data Science Speaker Series at the LBJ School of Public Affairs. Co-sponsors also include UT Library Research Data Services and Mission Capital.
Friday 5/3, 12:15-13:30, SRH 3.122 (lunch provided)
Investigating Women’s Unmet Need for Contraceptives in Haiti
Predicting the Number of Crisis Pregnancy Centers by State
Where is the Relief? The Humanitarian Response to Violence in Syria and Regional Refugee Flows
Presentation slides here
Dr. Thomas C. is a Lead Scientist in the CIA’s Directorate of Analysis and holds a Ph.D. in Economics. The talk will focus on how the Intelligence Community (IC) manages data, including some of the unique aspects in the IC. How the IC generates insights: typical timelines, customers, and general descriptions of modeling techniques, as well as how the IC integrates social science research.
Date: Friday, April 26, 2019
Time: 12:15 – 1:30pm (lunch provided)
Location: LBJ School of Public Affairs, 1st floor, Room SRH 3.122
Please RSVP closed. Presentation slides here
Political elites in a networked society: How Chinese civil society is integrated with the authoritarian regime
Thursday, March 21
6:00pm – 8:00pm
LBJ Washington Center
1100 New York Ave NW
Light refreshments served
This paper studies how the Chinese civil society is integrated with the authoritarian regime through a highly educated group of political elites holding critical roles in both polity and civil society. Analysis of individuals presents that, the political elites are meshed in a social structure of two-layer networks: the civil society network and the political network. The leaders of Communist Youth League are widely embedded in civil society network but marginalized in political network. Over half of these political elites are provincial leaders connecting local and central governments. Analysis of formal institutions reveals that, Chinese Communist Party (CCP) forms a dyad with the State Council, resembling the politics–administration tension studied in western democracies. Unlike conventional thoughts about authoritarian regimes, the Chinese civil society and political networks are highly pluralistic, but CCP builds itself as a necessary broker between political groups. In President Hu’s term, intellectuals are a significant power for integrating civil society. In Xi’s term, CCP is over-politicized, widely embedded, and institutionalized, serving as the only and direct channel that connects civil society and polity.
Please enter the building through the New York Ave NW entrance. The Center is located one level up via the stairs or elevator immediately to your right upon entrance.
Metro Access – The LBJ Washington Center is located two blocks from Metro Center (Red, Blue, Orange, and Silver lines) and a 10-minute walk from Gallery Place/Chinatown (Green and Yellow lines)
The RGK Center’s Data Science Speaker Series welcomes Dr. Jesse Lecy, co-founder of the Nonprofit Open Data Collective to present his research paper titled “The Political Economy of Nonprofit Entrepreneurship: Using Open Data to Explore the Geographic and Demographic Dimensions of Nonprofit Open Data Collective”.