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HIRAISHI Kai

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07 Apr 2023
STAGE 1

The WEIRD problem in a “non-WEIRD” context: A meta-research on the representativeness of human subjects in Chinese psychological research

How well do "non-WEIRD" participants in multi-lab studies represent their local population?

Recommended by based on reviews by Zoltan Dienes, Patrick Forscher and Kai Hiraishi
In this protocol, Yue et al. (2023) aim to clarify whether the sample of non-WEIRD countries included in multi-lab studies is actually representative of those countries and cultures. Focusing on China, this study will compare Chinese samples in several multi-lab studies with participants in studies published in leading national Chinese journals on various aspects, including demographic data and geographic information. This work will provide useful information on the extent to which multi-lab studies are able to deal with generalizability, especially as they intend to address the generalizability problem.
 
The Stage 1 manuscript was reviewed by three experts, including two with an interest in the WEIRD problem and a wealth of experience in open science and multi-lab research, plus an expert in Bayesian statistics, which this manuscript uses. Following multilpe rounds of peer review, and based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).
 
URL to the preregistered Stage 1 protocol: https://osf.io/ehw54
 
Level of bias control achieved: Level 4. At least some of the data/evidence that will be used to answer the research question already exists AND is accessible in principle to the authors (e.g. residing in a public database or with a colleague) BUT the authors certify that they have not yet accessed any part of that data/evidence.
 
List of eligible PCI RR-friendly journals: 
 
 
References
 
Yue, L., Zuo, X.-N., & Hu, C.-P. (2023) The WEIRD problem in a “non-WEIRD” context: A meta-research on the representativeness of human subjects in Chinese psychological research, in principle acceptance of Version 7 by Peer Community in Registered Reports. https://osf.io/ehw54
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HIRAISHI Kai

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