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Digital pathways beyond Western-centric participants
Edmond Awad1,2,3
1Department of Economics, University of Exeter, Exeter, UK. e.awad@exeter.ac.uk.
Social science research still oversamples Western, educated, industrialised, rich, and democratic (WEIRD) individuals. This article explores digital tools to overcome sampling biases and include diverse global participants in studies.
Area of Science:
- Social and behavioral sciences
- Psychology
- Anthropology
Background:
- The seminal 2010 article by Henrich et al. highlighted the oversampling of Western, Educated, Industrialized, Rich, and Democratic (WEIRD) individuals in social and behavioral science research.
- Despite awareness, recent reviews show persistent sampling biases, with a low proportion of participants from non-Western countries in leading psychology journals.
- This reliance on WEIRD populations limits the generalizability of research findings.
Purpose of the Study:
- To address the persistent sampling bias in social and behavioral sciences towards WEIRD populations.
- To explore the potential of the digital age in facilitating research with diverse, non-WEIRD participants.
- To provide an overview of digital tools for inclusive global research and discuss their pros and cons.
Main Methods:
- Review of literature on sampling biases in social sciences.
- Identification and analysis of digital tools and platforms for participant recruitment.
- Qualitative assessment of the advantages and disadvantages of various digital tools.
Main Results:
- The digital age offers numerous opportunities to recruit participants from diverse, non-WEIRD backgrounds.
- Various digital tools can facilitate and support social science research globally.
- Each tool presents unique advantages and disadvantages that need careful consideration.
Conclusions:
- The persistent sampling bias in social sciences requires active intervention.
- Digital tools offer viable solutions to enhance participant diversity and global representation in research.
- Researchers should critically evaluate and strategically employ digital tools to mitigate WEIRD sampling biases.
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