logo
ResearchBunny Logo
Fair algorithms for selecting citizens’ assemblies

Computer Science

Fair algorithms for selecting citizens’ assemblies

B. Flanigan, P. Gölz, et al.

Discover groundbreaking algorithms designed by Bailey Flanigan, Paul Gölz, Anupam Gupta, Brett Hennig, and Ariel D. Procaccia. These innovative solutions enhance fairness in selecting citizens' assemblies, balancing representativeness with equal selection probabilities. Join us in exploring a method that's already made waves in over 40 assemblies worldwide!

00:00
00:00
Playback language: English
Citation Metrics
Citations
0
Influential Citations
0
Reference Count
0

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

Related Publications

Explore these studies to deepen your understanding of the subject.

Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery
Medicine and Health

Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery

C. Boissin, L. Laflamme, et al.

The FAIR Cookbook - the essential resource for and by FAIR doers
Biology

The FAIR Cookbook - the essential resource for and by FAIR doers

P. Rocca-serra, W. Gu, et al.

Introducing the FAIR Principles for research software
Computer Science

Introducing the FAIR Principles for research software

M. Barker, N. P. C. Hong, et al.

Modeling community standards for metadata as templates makes data FAIR
Computer Science

Modeling community standards for metadata as templates makes data FAIR

M. A. Musen, M. J. O'connor, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny