Diverse perspectives from diverse scholars are vital for theoretical biology

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3 Scopus citations

Abstract

Science is based on studying some aspects of the world while holding others constant. The assumptions of what can and cannot be ignored implicitly shape our understanding of the world around us. This truth is particularly evident when studying biology through mathematical models, where one must explicitly state assumptions during the process of model building. Although we often recognize that all models are “wrong” in their assumptions, we often overlook the corollary that developing multiple models that are wrong in different ways can help us triangulate truth in our understanding. Theoretical biologists build models in the image of how they envision the world, an image that is shaped by their scientific identity, experiences, and perspectives. A lack of diversity in any of these axes handicaps our ability to understand biological systems through theory. However, we can overcome this by collectively recognizing our own assumptions, by understanding how perspective shapes the development of theory, and — most importantly — by increasing the diversity of theoretical biologists (in terms of identity, experiences, and perspectives). Combined, this will lead to developing theory that provides a richer understanding of the biological world.

Original languageEnglish (US)
Pages (from-to)143-146
Number of pages4
JournalTheoretical Ecology
Volume15
Issue number2
DOIs
StatePublished - Jun 2022

Bibliographical note

Funding Information:
I thank Daniel Stanton for many insightful conversations, María Rebolleda-Gómez for helpful feedback on an early draft, and two anonymous reviewers for feedback. I am grateful for the extra time to think enabled by a sabbatical from the University of Minnesota, and to the new perspective gained from being on sabbatical at l’Université de Montréal with support from Fulbright Canada.

Funding Information:
This study was supported by Fulbright Canada.

Publisher Copyright:
© 2022, The Author(s).

Keywords

  • Assumptions
  • Bias
  • Diversity
  • Mathematical model
  • Theory

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