Header

UZH-Logo

Maintenance Infos

Making Wakefield Workable: The Fitness and Function Framework for Taxonomising Evolutionary Dysfunction


Hunt, Adam (2023). Making Wakefield Workable: The Fitness and Function Framework for Taxonomising Evolutionary Dysfunction. PsyArXiv Preprints 27 07 2023, Cornell University.

Abstract

Jerome Wakefield’s ‘Harmful Dysfunction Analysis’ (HDA) recognises biological and psychological disorder exists wherever two conditions are met: concurrent harm, a subjective value component, and dysfunction, an objective component related to the interruption of evolutionarily selected effects. This is arguably the leading definition of disorder, and is prominently referenced in evolutionary psychiatry, yet suffers various criticisms. These particularly concern the ‘dysfunction’ component, which is undermined by the indeterminacy of ancestral function and a range of complex counter-examples, particularly relating to mismatch, by-products and extremes of adaptive spectrums. To tackle these criticisms, I provide a definitional framework which allows clear pathways to dysfunction attribution in the cases problematic for Wakefield. The key move here is distinguishing biological objects with fitness, a fundamentally quantifiable variable, from the selective processes of function and dysfunction which lead to that fitness, which rely on qualitative descriptions, and are much harder to exactly specify and demarcate to the level of precision necessary for the HDA. I also note the importance of specifying framing environments and trait descriptions. The resulting framework solves various problems with Wakefield’s account and leads to a taxonomy of different classes of dysfunction. This is unique amongst existing evolutionary taxonomies of disorder by offering strict demarcation, exclusivity and greater theoretical completeness. By relying ultimately on fitness effects rather than descriptions of dysfunctional processes and recognising distinct possible classes of evolutionary dysfunction, a more tractable direction for scientific investigation into any trait’s dysfunctional status is offered, with the potential to make Wakefield’s HDA workable.

Abstract

Jerome Wakefield’s ‘Harmful Dysfunction Analysis’ (HDA) recognises biological and psychological disorder exists wherever two conditions are met: concurrent harm, a subjective value component, and dysfunction, an objective component related to the interruption of evolutionarily selected effects. This is arguably the leading definition of disorder, and is prominently referenced in evolutionary psychiatry, yet suffers various criticisms. These particularly concern the ‘dysfunction’ component, which is undermined by the indeterminacy of ancestral function and a range of complex counter-examples, particularly relating to mismatch, by-products and extremes of adaptive spectrums. To tackle these criticisms, I provide a definitional framework which allows clear pathways to dysfunction attribution in the cases problematic for Wakefield. The key move here is distinguishing biological objects with fitness, a fundamentally quantifiable variable, from the selective processes of function and dysfunction which lead to that fitness, which rely on qualitative descriptions, and are much harder to exactly specify and demarcate to the level of precision necessary for the HDA. I also note the importance of specifying framing environments and trait descriptions. The resulting framework solves various problems with Wakefield’s account and leads to a taxonomy of different classes of dysfunction. This is unique amongst existing evolutionary taxonomies of disorder by offering strict demarcation, exclusivity and greater theoretical completeness. By relying ultimately on fitness effects rather than descriptions of dysfunctional processes and recognising distinct possible classes of evolutionary dysfunction, a more tractable direction for scientific investigation into any trait’s dysfunctional status is offered, with the potential to make Wakefield’s HDA workable.

Statistics

Citations

Dimensions.ai Metrics

Altmetrics

Downloads

64 downloads since deposited on 22 Nov 2023
65 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Working Paper
Communities & Collections:04 Faculty of Medicine > Institute of Evolutionary Medicine
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2023
Deposited On:22 Nov 2023 19:01
Last Modified:22 Nov 2023 19:01
Series Name:PsyArXiv Preprints
ISSN:0010-9452
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.31234/osf.io/qbgke
  • Content: Submitted Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)