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The Propensity Interpretation of Fitness and the Propensity Interpretation of Probability

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Abstract

The paper provides a new critical perspective on the propensity interpretation of fitness (PIF), by investigating its relationship to the propensity interpretation of probability. Two main conclusions are drawn. First, the claim that fitness is a propensity cannot be understood properly: fitness is not a propensity in the sense prescribed by the propensity interpretation of probability. Second, this interpretation of probability is inessential for explanations proposed by the PIF in evolutionary biology. Consequently, interpreting the probabilistic dimension of fitness in terms of propensities is neither a strong motivation in favor of this interpretation, nor a possible target for substantial criticism.

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Notes

  1. Major criticisms are developed in: Humphreys (1985), Kyburg (2002), Eagle (2004), Humphreys (2004). For discussion of such objections, see Berkovitz’s paper in this volume.

  2. See Richardson and Burian (1992), Brandon and Carson (1996).

  3. Brandon (1978) is also an early paper in the PIF tradition. Yet, even though he mentions propensities in connection with fitness and cites Popper (1959), this paper deals neither specifically, nor explicitly with the claim that fitness is a propensity.

  4. We cannot use Coffa (1977), that is cited by Mills and Beatty, as our reference concerning propensities because it is not about probability and does not define or support a version of the propensity interpretation of probability.

  5. The expected number of offspring is certainly not a good measure of fitness: other parameters, like variance, are relevant too. However, we shall not enter the debate concerning the statistic(s) that should enter measures of fitness: the initial suggestion to the effect of defining fitness in terms of expectation suffices to raise the questions we are interested in. For a critical discussion of the idea that fitness is measured by the expected number of offspring, see Beatty and Finsen (1989), Richardson and Burian (1992), Sober (2001).

  6. Strictly speaking, the disposition of salt to dissolve in water is not deterministic: the probability of dissolution is not 1. However, this probability is extremely close to 1 and the quotation above (p. 271) clearly shows that Beatty and Mills take it to be deterministic.

  7. In particular, some authors argue that disposition ascriptions are just a way of talking about intrinsic properties of objects (Quine 1974; Boyle 1666/1979). Others claim that, although dispositions are more than just names we use to refer to categorical properties, they are causally impotent (O’Shaughnessy 1970; Prior et al. 1982). For a complete review of objections to the view that dispositions are causally efficacious, and for an argument in favour of this view, see Mumford (1998, chapter 6).

  8. More generally, the idea that events with higher probabilities are better explained has been discarded by critics of the inductive-statistical account of explanation (e.g., Salmon 1971, Coffa 1977, Railton 1978).

  9. It is true that differences in probabilities could appear in the explanation of differences in relative frequencies of various offspring contributions. Think about repeating similar circumstances. Then, the larger the number of repetitions, the higher the probability that the actual amount of offspring will correspond to the expectation. Moreover, the larger a population of similar individuals, the higher the chance that the average number of offspring will be close to the expectation. Those explanatory relations, however, are irrelevant as far as the explanation of differences in individual reproductive success are concerned.

  10. Such an explanation, in any case, is not causal. Among the main kinds of explanation, inductive statistical seems to be the closest.

References

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Author notes

  1. Francesca Merlin

    Present address: Université Paris 1 Panthéon-Sorbonne & CNRS, UMR 8590 IHPST — Institut d‘histoire et de philosophie des sciences et des techniques, Paris, France

Authors and Affiliations

  1. Université Paris-Sorbonne, Paris, France

    Isabelle Drouet

  2. IHPST, 13 rue du Four, 75006, Paris, France

    Francesca Merlin

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  1. Isabelle Drouet
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Drouet, I., Merlin, F. The Propensity Interpretation of Fitness and the Propensity Interpretation of Probability. Erkenn 80 (Suppl 3), 457–468 (2015). https://doi.org/10.1007/s10670-014-9681-2

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