Dear Cognet Members,
My colleagues and I are recruiting co-authors and analysts for a crowd-sourced data analysis project that we think would interest some of you. You can see more information about the project and how to sign-up below; sign-ups will close on November 28th.
Best,
Emily Robinson
PhD Student in Organizational Behavior
INSEAD Europe Campus
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What happens when multiple independent analysts test the same hypothesis on the same dataset? Do they come up with the same results, or are the results heavily contingent on the specific analytic strategy chosen? If you're interested in being a part of finding out, you can sign up here to be a data analyst and co-author on our collaborative crowdsourcing project.
In the first crowdsourcing data analysis project, 29 teams of analysts examined whether soccer referees give more red cards to dark skin toned than light-skin toned players (Silberzahn et al., in preparation; see project page on the Open Science Framework at https://osf.io/gvm2z/). The outcome was striking: although 62% of teams obtained a significant effect in the expected direction, estimated effect sizes ranged from moderately large to practically nil.
Following the success of this first project, Brian Nosek, Eric Luis Uhlmann, Amy Sommer, Kaisa Snellman, David Robinson, Raphael Silberzahn, and I have launched a second crowdsourcing data analysis project. For this second project, we have collected the scientific dialogue from Edge.org to analyze how scientist gender and status affect intellectual conversations. This project adds several new key features to the first crowdsourcing analytics project, in particular having analysts operationalize key variables (e.g., dominant language) on their own and giving analysts the opportunity to propose and vote on their own hypothesis to be tested by the group.
The full project description is here. All analysts who complete the steps listed in the requirements will receive an author credit on the final paper. We would appreciate a variety of perspectives represented in the group. Also, please feel free to let others know about the opportunity; anyone with the relevant data analysis skills is welcome to take part.
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