Epistemic Landscapes, Optimal Search, and the Division of Cognitive Labor
Bibliographic Data
| ID | 10707809 |
|---|---|
| Authors | J Mckenzie Alexander (0000-0002-2663-6993, University of London), Johannes Himmelreich (0000-0002-2163-0082, University of London), Christopher Thompson (0000-0001-6970-5437, Ethics and Public Policy Center), Christopher G Thompson (0000-0002-6000-8499) |
| Year | 2015 |
| Volume | 82 |
| Issue | 3 |
| Pages | 424-453 |
| Publication date | 2015-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Philosophy of Science (JOURNAL) |
| Journal identifiers | ISSN: 0031-8248 • E-ISSN: 1539-767X |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1086/681766 |
| OpenAlex | W1991113915 |
| Language | EN |
| Citations received | 31 |
| References cited | 18 |
This article examines two questions about scientists’ search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, “Epistemic Landscapes and the Division of Cognitive Labor” (this journal, 2009), that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors that led to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments
Cognition · Division (mathematics) · Division of labour · Epistemology · Geography · Pace · Political science · Skepticism · Sociology · Evolutionary Game Theory and Cooperation · Experimental Behavioral Economics Studies · Game Theory and Applications · Law · Mathematics · Philosophy · Psychology
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Feyerabend’s well-ordered science
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Value of cognitive diversity in science
Information elaboration and epistemic effects of diversity
A mid-level approach to modeling scientific communities
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Diversity, Ability, and Expertise in Epistemic Communities
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Agent-based models of scientific interaction
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Group Performance and Decision Making
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Epistemic Landscapes and the Division of Cognitive Labor
The Advancement of Science
| Unique citing works | 31 |
|---|---|
| Citations per year | 3,1 |
| Citation span | 2016 - 2026 (11) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 31 |