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Discovering the unknown unknowns of research cartography with high-throughput natural description.
Katiyar, Tanay; Bonnefon, Jean-François; Mehr, Samuel A; Singh, Manvir.
Afiliação
  • Katiyar T; Institut Jean Nicod, Département d'études cognitives, École normale supérieure (ENS-PSL), Paris, France tanay.katiyar20@gmail.com.
  • Bonnefon JF; Toulouse School of Economics, Centre National de la Recherche Scientifique (TSM-R), Toulouse, France jean-francois.bonnefon@tse-fr.eu; https://jfbonnefon.github.io.
  • Mehr SA; School of Psychology, University of Auckland, Auckland, New Zealandhttps://mehr.nz/.
  • Singh M; Yale Child Study Center, Yale University, New Haven, CT, USA sam@yale.edu.
Behav Brain Sci ; 47: e50, 2024 Feb 05.
Article em En | MEDLINE | ID: mdl-38311444
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 experiment design.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article