‘Extreme’ Organisms and the Problem of Generalization: Interpreting the Krogh Principle

Sara Green, Michael Dietrich, Sabina Leonelli, Rachel Ankeny

13 Citationer (Scopus)
48 Downloads (Pure)

Abstract

Many biologists appeal to the so-called Krogh principle when justifying their choice of experimental organisms. The principle states that “for a large number of problems there will be some animal of choice, or a few such animals, on which it can be most conveniently studied”. Despite its popularity, the principle is often critiqued for implying unwarranted generalizations from optimal models. We argue that the Krogh principle should be interpreted in relation to the historical and scientific contexts in which it has been developed and used. We interpret the Krogh Principle as a heuristic, i.e., as a recommendation to approach biological problems through organisms where a specific trait or physiological mechanism is expected to be most distinctively displayed or most experimentally accessible. We designate these organisms “Krogh organisms”. We clarify the differences between uses of model organisms and non-standard Krogh organisms. Among these is the use of Krogh organisms as “negative models” in biomedical research, where organisms are chosen for their dissimilarity to human physiology. Importantly, the representational scope of Krogh organisms and the generalizability of their characteristics are not fixed or assumed but explored through experimental studies. Research on Krogh organisms is steeped in the comparative method characteristic of zoology and comparative physiology, in which studies of biological variation produce insights into general physiological constraints. Accordingly, we conclude that the Krogh principle exemplifies the advantages of studying biological variation as a strategy to produce generalizable insights.

OriginalsprogEngelsk
Artikelnummer65
TidsskriftHistory and Philosophy of the Life Sciences
Vol/bind40
Udgave nummer4
Sider (fra-til)1-22
Antal sider22
ISSN0391-9714
DOI
StatusUdgivet - 1 dec. 2018

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