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A critical review of the statisticalist debate

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Abstract

Over the past decade philosophers of biology have discussed whether evolutionary theory is a causal theory or a phenomenological study of evolution based solely on the statistical features of a population. This article reviews this controversy from three aspects, respectively concerning the assumptions, applications, and explanations of evolutionary theory, with a view to arriving at a definite conclusion in each contention. In so doing I also argue that an implicit methodological assumption shared by both sides of the debate, namely the overconfidence in conceptual analysis as a tool to understand the scientific theory, is the real culprit that has both generated the problem and precluded its solution for such a long time.

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Notes

  1. See e.g., Okasha (2006) for a derivation of the Price equation.

  2. Hence the model defines fitness as a measure of the actual number of offspring causally related to phenotype, contradicting the common philosophical wisdom according to which fitness is the expected offspring number that supervenes on phenotype and the environment. This discrepancy will be discussed in section “Much ado about fitness”.

  3. An empirical application of the Price equation can be found in Morrissey et al. (2012), but it is for the purpose of a post-hoc check of predicted adaptive responses, and not for predicting evolutionary response or detecting a selective pressure.

  4. For this reason some statisticalists, e.g., Walsh (2007, p. 288), avoid taking this approach.

  5. The precise definition given by Woodward (2003) is more nuanced than this due primary to a possible violation of faithfulness, but these details can be ignored here.

  6. Note that this differs from the question regarding the causal basis or propensity interpretation of fitness as discussed above (section “The causal basis of fitness”), which asks whether phenotype can be a cause of fitness.

  7. Though not mentioned in his paper, a criterion similar to Walsh’s was already proposed by Cartwright (1979) and criticized by Dupré (1984).

  8. Matthen and Ariew attribute this definition to Sober (1984, pp. 21–22), but I couldn’t locate it in the pages they point to.

  9. However, since interventions on these error terms count at the same time as soft-interventions on fitness, they may also affect the rate of adaptive response if they change the mean fitness. I thank Bruce Glymour for pointing this out.

  10. Speed in this case, however, must be causally disconnected (or d-separated; Pearl 2000) from the skin thickness for predators’ attack to be an indiscriminate sampling of the latter. Otherwise there is an indirect selection of skin thickness (Sober 1984).

  11. Environmental factors in the causal graph represent these aspects of environment that are “experienced” by each individual, and are properties of individuals in this sense.

  12. I thank Patrick Forber for bringing my attention to this similarity.

  13. This does not mean, however, the causal exclusion problem does not exist in evolutionary biology. A similar problem, for example, emerges in the debate over levels of selection, i.e., whether group properties may have fitness contribution irreducible to individual properties (Okasha 2006). This is an open interesting question, but should be distinguished from the statisticalist debate.

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Acknowledgments

I thank Patrick Forber, Charles Pence, and the members of Griesemer/Millstein philbio lab at UC Davis for their helpful comments on earlier versions of this paper.

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  1. Philosophy Department, Kobe University, 1-1 Rokkodai-machi, Nada, Kobe, Japan

    Jun Otsuka

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Otsuka, J. A critical review of the statisticalist debate. Biol Philos 31, 459–482 (2016). https://doi.org/10.1007/s10539-016-9528-0

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