Accelerating Computational Reproducibility in Economics

CSS Training Program

Speaker(s)

Katie Hoeberling

Program Manager, BITSS

Katie Hoeberling leads fundraising, partnership development, training initiatives, and the Catalyst Program for the Berkeley Initiative for Transparency in the Social Sciences (BITSS). She previously served as a Borlaug Fellow in Global Food Security studying savings-led microfinance and farmer-centered innovation initiatives in Cambodia, supported an environmental impact assessment of California almonds and the revision of the Urban Forest Project Protocol for the California carbon market, and worked with the Food Chain Workers Alliance and the Los Angeles Food Policy Council. Katie holds an MSc in International Agricultural Development from UC Davis and a BSc in Environmental Science from UCLA.

Fernando Hoces de la Guardia

Project Scientist, BITSS

Fernando Hoces de la Guardia is a Project Scientist for the Berkeley Initiative for Transparency in the Social Sciences (BITSS). He works on bridging research-to-policy gaps in regards to transparency and reproducibility and improving the computational reproducibility of economics research. He received his Ph.D. in Policy Analysis from the Pardee RAND Graduate School where his research focused on increasing the transparency and reproducibility of policy analysis as a way to strengthen the connection between policy and evidence. Before RAND, he studied economics and conducted impact evaluations and economic analyses of various social policies. He has also supported BITSS-led trainings in the past and led a series of Catalyst trainings in South America in 2017.

Monday, October 12, 2020

Computational Social Science Forum
Date: Monday, October 12, 2020
Time: 12:00-1:30 PM Pacific Time
Location: Live Webcast
Speakers: Katie Hoeberling and Fernando Hoces de la Guardia, Berkeley Initiative for Transparency in the Social Sciences (BITSS)

BITSS launched the Accelerating Computational Reproducibility in Economics (ACRE) project in collaboration with American Economic Association (AEA) Data Editor Lars Vilhuber. ACRE supports social science researchers in meeting journal editorial expectations of pre-publication verification of computational reproducibility. ACRE builds capacity for social science researchers and is developing the Social Science Reproduction platform, an online tool for systematically sourcing and recording the results of attempts to verify the computational reproducibility of published work. Authors: Aleks Bogdanoski, Joel Ferguson, Fernando Hoces (presenter), Katie Hoeberling, Edward Miguel (PI), Emma Ng, Lars Vilhuber (Co-PI).

The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Weekly meetings are hosted by researchers from BIDS and D-Lab, and participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. We welcome social scientists researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. This Forum is organized as part of the Computational Social Science Training Program. Meetings are currently held virtually on Mondays at 12:00-1:30 PM Pacific Time, and interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact css-t32@berkeley.edu for more information.

Computational Social Science

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