The division of linguistic labour for offloading conceptual understanding

Edgar J. Andrade-Lotero, Julián M. Ortiz-Duque, Javier A. Velasco-García, Robert L. Goldstone

Research output: Contribution to journalResearch Articlepeer-review

8 Scopus citations

Abstract

The division of linguistic labour (DLL), initially theorized by philosophers, has gained the attention of cognitive scientists in the last decade. Contrary to some controversial philosophical accounts of DLL, we propose that it is an extended mind strategy of offloading conceptual understanding onto other people. In this article, we empirically explore this proposal by providing an exploratory experimental paradigm to search for the mechanisms underwriting DLL and how they may work in practice. We developed a between-subjects experiment in which participants had to categorize two pairs of highly confusable dog breeds after receiving categorization training on just one pair of breeds. In the treatment group, participants were grouped in dyads and were allowed to interact with each other by means of the labels of these four dog breeds. In their queries to trained 'experts', novices frequently used labels to refer to breeds that they could not identify themselves. Experts were highly responsive to their paired novices' queries, and the rates of querying for the two members within a dyad were positively correlated. Independent categorization failure and offloading categorization success lead to subsequent increases in querying by novices, indicating adaptive use of offloading. Self-reports of breed knowledge were higher for experts within a dyad compared to isolated experts. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Translated title of the contributionLa división de la labor lingüística para la descarga de comprensión conceptual
Original languageEnglish (US)
Article number20210360
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Volume378
Issue number1870
DOIs
StatePublished - Dec 26 2022

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences

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