I describe a realist, ontologically objective interpretation of probability, "far-flung frequency (FFF) mechanistic probability". FFF mechanistic probability is defined in terms of facts about the causal structure of devices and certain sets of frequencies in the actual world. Though defined partly in terms of frequencies, FFF mechanistic probability avoids many drawbacks of well-known frequency theories and helps causally explain stable frequencies, which will usually be close to the values of mechanistic probabilities. I also argue that it's a virtue rather than (...) a failing of FFF mechanistic probability that it does not define single-case chances, and compare some aspects of my interpretation to a recent interpretation proposed by Strevens. (shrink)
Organisms' environments are thought to play a fundamental role in determining their fitness and hence in natural selection. Existing intuitive conceptions of environment are sufficient for biological practice. I argue, however, that attempts to produce a general characterization of fitness and natural selection are incomplete without the help of general conceptions of what conditions are included in the environment. Thus there is a "problem of the reference environment"—more particularly, problems of specifying principles which pick out those environmental conditions which determine (...) fitness. I distinguish various reference environment problems and propose solutions to some of them. While there has been a limited amount of work on problems concerning what I call "subenvironments", there appears to be no earlier work on problems of what I call the "whole environment". The first solution I propose for a whole environment problem specifies the overall environment for natural selection on a set of biological types present in a population over a specified period of time. The second specifies an environment relevant to extinction of types in a population; this kind of environment is especially relevant to certain kinds of long-term evolution. (shrink)
One controversy about the existence of so called evolutionary forces such as natural selection and random genetic drift concerns the sense in which such “forces” can be said to interact. In this paper I explain how natural selection and random drift can interact. In particular, I show how population-level probabilities can be derived from individual-level probabilities, and explain the sense in which natural selection and drift are embodied in these population-level probabilities. I argue that whatever causal character the individual-level probabilities (...) have is then shared by the population-level probabilities, and that natural selection and random drift then have that same causal character. Moreover, natural selection and drift can then be viewed as two aspects of probability distributions over frequencies in populations of organisms. My characterization of population-level probabilities is largely neutral about what interpretation of probability is required, allowing my approach to support various positions on biological probabilities, including those which give biological probabilities one or another sort of causal character. ‡This paper has benefited from feedback on and discussions of this and earlier work. I want to thank André Ariew, Matt Barker, Lindley Darden, Patrick Forber, Nancy Hall, Mohan Matthen, Samir Okasha, Jeremy Pober, Robert Richardson, Alex Rosenberg, Eric Seidel, Denis Walsh, and Bill Wimsatt. †To contact the author, please write to: Department of Philosophy, University of Alabama at Birmingham, HB 414A, 900 13th Street South, Birmingham, AL 35294-1260; e-mail: [email protected]. (shrink)
It has been argued that biological fitness cannot be defined as expected number of offspring in all contexts. Some authors argue that fitness therefore merely satisfies a common schema or that no unified mathematical characterization of fitness is possible. I argue that comparative fitness must be relativized to an evolutionary effect; thus relativized, fitness can be given a unitary mathematical characterization in terms of probabilities of producing offspring and other effects. Such fitnesses will sometimes be defined in terms of probabilities (...) of effects occurring over the long term, but these probabilities nevertheless concern effects occurring over the short term. †To contact the author, please write to: Department of Philosophy, University of Alabama at Birmingham, HB 414A, 900 13th Street South, Birmingham, AL 35294‐1260; e‐mail: [email protected]. (shrink)
Recent debate on the nature of probabilities in evolutionary biology has focused largely on the propensity interpretation of fitness (PIF), which defines fitness in terms of a conception of probability known as “propensity”. However, proponents of this conception of fitness have misconceived the role of probability in the constitution of fitness. First, discussions of probability and fitness have almost always focused on organism effect probability, the probability that an organism and its environment cause effects. I argue that much of the (...) probability relevant to fitness must be organism circumstance probability, the probability that an organism encounters particular, detailed circumstances within an environment, circumstances which are not the organism’s effects. Second, I argue in favor of the view that organism effect propensities either don’t exist or are not part of the basis of fitness, because they usually have values close to 0 or 1. More generally, I try to show that it is possible to develop a clearer conception of the role of probability in biological processes than earlier discussions have allowed. (shrink)
It’s recently been argued that biological fitness can’t change over the course of an organism’s life as a result of organisms’ behaviors. However, some characterizations of biological function and biological altruism tacitly or explicitly assume that an effect of a trait can change an organism’s fitness. In the first part of the paper, I explain that the core idea of changing fitness can be understood in terms of conditional probabilities defined over sequences of events in an organism’s life. The result (...) is a notion of “conditional fitness” which is static but which captures intuitions about apparent behavioral effects on fitness. The second part of the paper investigates the possibility of providing a systematic foundation for conditional fitness in terms of spaces of sequences of states of an organism and its environment. I argue that the resulting “organism–environment history conception” helps unify diverse biological perspectives, and may provide part of a metaphysics of natural selection. (shrink)
This chapter explores a philosophical hypothesis about the nature of (some) probabilities encountered in social sciences. It should be of interest to those with philosophical concerns about the foundations of probability, and to social scientists and philosophers of science who are somewhat puzzled by the nature of probability in social domains. As will become clear below, the chapter is not intended as a contribution to an empirical methodology such as a particular way of applying statistics.
and was correct to conclude that the way a biological population is described should affect conclusions about whether natural selection occurs, but wrong to conclude that natural selection is therefore not a cause. After providing a new argument that ignored crucial biological details, I give a biological illustration that motivates a fairly extreme dependence on description. I argue that contrary to an implication of , biologists allow much flexibility in describing populations, as contemporary research on recent human evolution shows. Properly (...) understood, such description-dependence is consistent with descriptions capturing different causal relations involving the same population. I thus show that Walsh’s arguments fail for reasons that have not previously been understood; I argue that Walsh’s more recent “Sure Thing” argument fails for similar reasons. The resulting view provides a new perspective on causation in evolutionary processes. (shrink)
I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)
One finds intertwined with ideas at the core of evolutionary theory claims about frequencies in counterfactual and infinitely large populations of organisms, as well as in sets of populations of organisms. One also finds claims about frequencies in counterfactual and infinitely large populations—of events—at the core of an answer to a question concerning the foundations of evolutionary theory. The question is this: To what do the numerical probabilities found throughout evolutionary theory correspond? The answer in question says that evolutionary probabilities (...) are “hypothetical frequencies” (including what are sometimes called “long-run frequencies” and “long-run propensities”). In this paper, I review two arguments against hypothetical frequencies. The arguments have implications for the interpretation of evolutionary probabilities, but more importantly, they seem to raise problems for biologists’ claims about frequencies in counterfactual or infinite populations of organisms and sets of populations of organisms. I argue that when properly understood, claims about frequencies in large and infinite populations of organisms and sets of populations are not threatened by the arguments. Seeing why gives us a clearer understanding of the nature of counterfactual and infinite population claims and probability in evolutionary theory. (shrink)
Sewall Wright ’s FST is a mathematical test widely used in empirical applications to characterize genetic and other diﬀerences between subpopulations, and to identify causes of those diﬀerences. Cockerham and Weir’s popular approach to statistical estimation of FST is based on an assumption sometimes formulated as a claim that actual populations tested are sampled from.
I investigate the structure of an argument that culture cannot be maintained in a population if each individual learns only from a single person. This appears to conflict with many models of cultural transmission and real-world cases. I resolve the first problem by showing that one of the models central to the argument is conceptually analogous and mathematically equivalent to one used to investigate the evolution of sexual reproduction. I resolve the second by arguing that probabilistic models of epistemological coherence (...) can be reinterpreted as models of support between cultural variants—illustrating the idea with a new model. (shrink)
Pseudorandom number generating algorithms play crucial roles in computer modeling and statistical modeling, but they have received little attention from philosophers of science. I revisit an argument that the success of practices in evolutionary biology using such algorithms in computer simulations provides evidence that evolutionary processes incorporate objective probabilities. I discuss the kind of stochasticity that pseudorandom number generators provide--what I call "pseudochance"--and argue that the argument from simulation practice, as well as other arguments, supports the view that evolutionary processes (...) incorporate pseudochance. I suggest that similar arguments might be given in other domains of science. (shrink)
Smaldino suggests that patterns that give rise to group-level cultural traits can also increase individual-level cultural diversity. I distinguish social roles and related social network structures and discuss ways in which each might maintain diversity. I suggest that cognitive analogs of “cohesion,” a property of networks that helps maintenance of diversity, might mediate the effects of social roles on diversity.
Background on probability and evolution -- Laying the foundation. Population-environment systems ; Causal probability and empirical practice ; Irrelevance of fitness as a causal property of token organisms ; Roles of environmental variation in selection -- Reconstructing evolution and chance. Populations in biological practice: Pragmatic yet real ; Real causation in pragmatic population-environment systems ; Fitness concepts in measurement and modeling ; Chance in population-environment systems ; The input measure problem for MM-CCS chance -- Conclusion.
Focus on the way in which cultural variants affect other variants' probabilities of transmission in modeling and empirical work can enrich Kline's conceptualization of teaching. For example, the problem of communicating complex cumulative culture is an adaptive problem; teaching methods that manage transmission so that acquisition of some cultural variants increases the probability of acquiring others, provide a partial solution.
Research in evolutionary ecology on random foraging seems to ignore the possibility that some random foraging is an adaptation not to environmental randomness, but to what Wimsatt called “perceived randomness”. This occurs when environmental features are unpredictable, whether physically random or not. Mere perceived randomness may occur, for example, due to effects of climate change or certain kinds of static landscape variation. I argue that an important mathematical model concerning random foraging doesn’t depend on environmental randomness, despite contrary remarks by (...) researchers. I use computer simulations to illustrate the idea that random foraging is an adaptation to mere perceived randomness. (shrink)