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Introduction to causality in science studies

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  • Klebel, Thomas
  • Traag, Vincent

Abstract

Sound causal inference is crucial for advancing the study of science. Incorrectly interpreting predictive effects as causal might be ineffective or even detrimental to policy recommendations. Many publications in science studies lack appropriate methods to substantiate their causal claims. We here provide an introduction to structural causal models. Such models, usually represented in a graphical form, allow researchers to make their causal assumptions transparent and provide a foundation for causal inference. We illustrate how to use structural causal models to conduct causal inference using regression models based on simulated data of a hypothetical structural causal model of Open Science. The graphical representation of structural causal models allows researchers to clearly communicate their assumptions and findings, thereby fostering further discussion. We hope our introduction helps more researchers in science studies to consider causality explicitly.

Suggested Citation

  • Klebel, Thomas & Traag, Vincent, 2024. "Introduction to causality in science studies," SocArXiv 4bw9e, Center for Open Science.
  • Handle: RePEc:osf:socarx:4bw9e
    DOI: 10.31219/osf.io/4bw9e
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    References listed on IDEAS

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    1. Marcus R. Munafò & George Davey Smith, 2018. "Robust research needs many lines of evidence," Nature, Nature, vol. 553(7689), pages 399-401, January.
    2. Cassidy R. Sugimoto & Chaoqun Ni & Terrell G. Russell & Brenna Bychowski, 2011. "Academic genealogy as an indicator of interdisciplinarity: An examination of dissertation networks in Library and Information Science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1808-1828, September.
    3. R. Dean Malmgren & Julio M. Ottino & Luís A. Nunes Amaral, 2010. "The role of mentorship in protégé performance," Nature, Nature, vol. 465(7298), pages 622-626, June.
    4. Heather A Piwowar & Roger S Day & Douglas B Fridsma, 2007. "Sharing Detailed Research Data Is Associated with Increased Citation Rate," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-5, March.
    5. Kwon, Seokbeom & Motohashi, Kazuyuki, 2021. "Incentive or disincentive for research data disclosure? A large-scale empirical analysis and implications for open science policy," International Journal of Information Management, Elsevier, vol. 60(C).
    6. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    7. Paul Hunermund & Elias Bareinboim, 2019. "Causal Inference and Data Fusion in Econometrics," Papers 1912.09104, arXiv.org, revised Mar 2023.
    8. Cassidy R. Sugimoto & Chaoqun Ni & Terrell G. Russell & Brenna Bychowski, 2011. "Academic genealogy as an indicator of interdisciplinarity: An examination of dissertation networks in Library and Information Science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(9), pages 1808-1828, September.
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