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Discovering the unknown unknowns of research cartography with high-throughput natural description

Author

Listed:
  • Tanay Katiyar

    (IJN - Institut Jean-Nicod - DEC - Département d'Etudes Cognitives - ENS Paris - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CdF (institution) - Collège de France - CNRS - Centre National de la Recherche Scientifique - Département de Philosophie - ENS Paris - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres)

  • Jean-François Bonnefon

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CNRS - Centre National de la Recherche Scientifique)

  • Samuel Mehr

    (University of Auckland [Auckland], Yale University [New Haven])

  • Manvir Singh

    (IAST - Institute for Advanced Study in Toulouse)

Abstract

To succeed, we posit that research cartography will require high-throughput natural description to identify unknown unknowns in a particular design space. High-throughput natural description, the systematic collection and annotation of representative corpora of real-world stimuli, faces logistical challenges, but these can be overcome by solutions that are deployed in the later stages of integrative experimental design.

Suggested Citation

  • Tanay Katiyar & Jean-François Bonnefon & Samuel Mehr & Manvir Singh, 2024. "Discovering the unknown unknowns of research cartography with high-throughput natural description," Post-Print hal-04551319, HAL.
    • Handle: RePEc:hal:journl:hal-04551319
    DOI: 10.1017/S0140525X23002170
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