Measurement Integrity in Peer Prediction: A Peer Assessment Case Study-Reference-Cited by-同舟云学术

Measurement Integrity in Peer Prediction: A Peer Assessment Case Study

Published:2023-07-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 24th ACM Conference on Economics and Computation
language:
Short-container-title:

Author:

Burrell Noah¹^ORCID,Schoenebeck Grant²^ORCID

Affiliation:

1. Computer Science & Engineering, University of Michigan, Ann Arbor, United States of America

2. School of Information, University of Michigan, Ann Arbor, United States of America

Funder

NSF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580507.3597744

Reference31 articles.

1. Rémi Bachelet Drissa Zongo and Aline Bourelle. 2015. Does peer grading work? How to implement and improve it? Rémi Bachelet Drissa Zongo and Aline Bourelle. 2015. Does peer grading work? How to implement and improve it?

2. Comparing instructor and peer assessment in MOOC GdP. In European MOOCs Stakeholders Summit 2015 (Proceedings of the Research Track). Mons Belgium. https://halshs.archives-ouvertes.fr/halshs-01146710 Comparing instructor and peer assessment in MOOC GdP. In European MOOCs Stakeholders Summit 2015 (Proceedings of the Research Track). Mons Belgium. https://halshs.archives-ouvertes.fr/halshs-01146710

3. Anujit Chakraborty Jatin Jindal and Swaprava Nath. 2020. Incentivizing Effort and Precision in Peer Grading. (2020). arXiv:1807.11657v6 [cs.GT] Working Paper. Anujit Chakraborty Jatin Jindal and Swaprava Nath. 2020. Incentivizing Effort and Precision in Peer Grading. (2020). arXiv:1807.11657v6 [cs.GT] Working Paper.

4. Crowdsourced judgement elicitation with endogenous proficiency

5. CrowdGrader

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dominantly Truthful Peer Prediction Mechanisms with a Finite Number of Tasks;Journal of the ACM;2023-12-23