Systematizing Confidence in Open Research and Evidence (SCORE)

Nazanin Alipourfard, Beatrix Arendt, Daniel Benjamin, Noam Benkler, Michael Metcalf Bishop, Mark Burstein, Martin Bush, James Caverlee, Yiling Chen and Chae Clark
Additional contact information
Beatrix Arendt: Center for Open Science
Noam Benkler: Smart Information Flow Technologies
Michael Metcalf Bishop: KeyW

No 46mnb, SocArXiv from Center for Open Science

Abstract: Assessing the credibility of research claims is a central, continuous, and laborious part of the scientific process. Credibility assessment strategies range from expert judgment to aggregating existing evidence to systematic replication efforts. Such assessments can require substantial time and effort. Research progress could be accelerated if there were rapid, scalable, accurate credibility indicators to guide attention and resource allocation for further assessment. The SCORE program is creating and validating algorithms to provide confidence scores for research claims at scale. To investigate the viability of scalable tools, teams are creating: a database of claims from papers in the social and behavioral sciences; expert and machine generated estimates of credibility; and, evidence of reproducibility, robustness, and replicability to validate the estimates. Beyond the primary research objective, the data and artifacts generated from this program will be openly shared and provide an unprecedented opportunity to examine research credibility and evidence.

Date: 2021-05-04
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:46mnb

DOI: 10.31219/osf.io/46mnb

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