Data-Informed Policymaking: Statisticians and Data Scientists Building & Communicating Evidence
Abstract Number:
1105
Submission Type:
Invited Panel Session
Participants:
Claire Bowen (1), Sally Morton (2), Lisa Mirel (3), Jeri Mulrow (4), Claire Bowen (1)
Institutions:
(1) Urban Institute, N/A, (2) Arizona State University, N/A, (3) N/A, N/A, (4) Westat, N/A
Chair:
Panelist(s):
Session Organizer:
Session Description:
Public policy initiatives advocating improved data access and use for data-informed decision making have recently gained momentum. Examples of such initiatives include the Evidence-Based Policymaking Act of 2018, the Advisory Committee on Data for Evidence Building Year 2 Report, America's Datahub Consortium, and the Committee on National Statistics panel focused on enhancing federal statistics and social and economic research in the 21st century. Despite the growing importance of data-driven approaches, many statisticians and data scientists remain uncertain about their role in these endeavors.
This panel aims to bridge this knowledge gap by convening experts from government, industry, and academia who will share their diverse perspectives on how statistics and data science can contribute to building robust evidence for informed public policy decision making, and how statisticians can be involved in the effective communication of that evidence. The discussions will highlight practical applications of data analytics and statistical methods in shaping effective policies. Furthermore, the panelists will provide valuable guidance to students and early career professionals seeking to pursue rewarding careers in the dynamic realm of public policy whether as statisticians, data scientists, or policy makers.
Sponsors:
Caucus for Women in Statistics 2
Government Statistics Section 1
Social Statistics Section 3
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Medium (80-150)
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
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