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Genetic conflicts and the case for licensed anthropomorphizing.

J Arvid Ågren1,2, Manus M Patten3

  • 1Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden.

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|December 6, 2022
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Summary
This summary is machine-generated.

Intentional language in biology, particularly in genetic conflicts, sparks debate. This study advocates for licensed anthropomorphism, merging creative agential thinking with rigorous mathematical modeling for evolutionary insights.

Keywords:
Gene’s-eye view of evolutionGenomic imprintingSelfish genetic elementsX chromosomes

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Area of Science:

  • Evolutionary Biology
  • Genetics
  • Philosophy of Science

Background:

  • The use of intentional language (e.g., agency, anthropomorphism) in biology is debated, with differing acceptance between fields like behavioral ecology and population genetics.
  • Genetic conflict research serves as a key area where these contrasting approaches intersect and create tension.

Purpose of the Study:

  • To review the debate surrounding intentional language in biology.
  • To examine the historical application of intentional language in genetic conflict studies, specifically genomic imprinting and sex chromosomes.
  • To propose a synthesized approach for using intentional language in evolutionary biology.

Main Methods:

  • Literature review of the intentional language debate in biology.
  • Historical analysis of genetic conflict research, focusing on genomic imprinting and sex chromosomes.
  • Conceptual synthesis of agential thinking and mathematical modeling.

Main Results:

  • The historical application of intentional language in genetic conflict research reveals a persistent tension between mechanistic and agential perspectives.
  • Genomic imprinting and sex chromosome evolution exemplify the challenges and opportunities presented by using intentional language in biological explanations.

Conclusions:

  • Advocates for a "licensed anthropomorphism" approach, integrating the explanatory power of agential thinking with the precision of formal mathematical models.
  • This synthesis aims to harness the creative potential of identifying evolutionary pressures while maintaining scientific rigor in biological studies.