Felsenstein’s method of independent contrasts (FIC) is one of the most widely used approaches to the study of correlated evolution. However, it is also quite controversial: numerous researchers have called various aspects of the method into question. Among these objections, there is one that, for two reasons, stands out from the rest: first, it is rather philosophical in nature; and second, it has received very little attention in the literature thus far. This objection concerns Sober’s charge that the FIC is (...) methodologically flawed due to its (seemingly) resting on the assumption that the traits it studies evolved by drift—and thus ruling out selective hypotheses from the start. In this article, I try to rebut this charge. To do this, I first consider a preliminary conceptual worry—the question of how it is even possible for two drift-driven traits to be evolutionarily correlated—and show that it can be answered by noting that the FIC can be seen as being concerned with the investigation of the modularity of the relevant traits. Given this, I then show that Sober’s methodological charge can at least be mitigated by noting that the assumptions behind the FIC do not in fact preclude it from investigating selective hypotheses. I end by pointing out that making this clearer is not just relevant for defending the cogency of the FIC, but also for developing a deeper understanding of correlated evolution in general. (shrink)

Due to the logical relations between theism and intelligent design (id), there are two challenges to theism that also apply to id. In the falsifiability challenge, it is charged that theism is compatible with every observation statement and thus asserts nothing. I argue that the contentious assumptions of this challenge can be avoided without loss of precision by charging theism (and thus id) directly with the lack of observational assertions. In the translatability challenge, it is charged that theism can be (...) translated into a (non-theistic) set of observation statements without loss of cognitive content. I argue that the contentious assumptions of this challenge are avoided by the related charge that the (non-theistic) evolutionary theory makes all the observational assertions of id, while the converse does not hold. Elliott Sober has argued that id meets the falsifiability challenge, but, since it makes almost no observational assertions, is not testable. I point out two problems with Sober’s argument and show that id is both deductively and probabilistically testable. Sober’s argument, I suggest, inconsistently combines the modified falsifiability challenge with the modified translatability challenge. If his claims about id’s observational assertions are true, however, id succumbs to the modified translatability challenge. (shrink)

Problem one: why, if God designed the human mind, did it take so long for humans to develop theistic concepts and beliefs? Problem two: why would God use evolution to design the living world when the discovery of evolution would predictably contribute to so much nonbelief in God? Darwin was aware of such questions but failed to see their evidential significance for theism. This paper explores this significance. Problem one introduces something I call natural nonbelief, which is significant because it (...) parallels and corroborates well-known worries about natural evil. Problems one and two, especially when combined, support naturalism over theism, intensify the problem of divine hiddenness, challenge Alvin Plantinga’s views about the naturalness of theism, and advance the discussion about whether the conflict between science and religion is genuine or superficial. (shrink)

Reverse inference is the most commonly used inferential strategy for bringing images of brain activation to bear on psychological hypotheses, but its inductive validity has recently been questioned. In this article, I show that, when it is analyzed in likelihoodist terms, reverse inference does not suffer from the problems highlighted in the recent literature, and I defend the appropriateness of treating reverse inference in these terms. 1 Introduction2 Reverse Inference3 Reverse Inference Defended3.1 Typical reverse inferences are fallacious3.2 No quick and (...) easy fix3.3 A likelihoodist defense of reverse inference3.4 An example4 Appropriateness of the Likelihoodist Approach4.1 Likelihoodist reverse inference is not applicable4.2 Cognitive neuroscientists are not interested in comparative conclusions4.3 Reverse inference and negative hypotheses4.4 Likelihoodist reverse inference may confuse cognitive neuroscientists4.5 Bayesian reverse inferences should be preferred to likelihoodist reverse inferences5 Conclusion. (shrink)

This paper considers a key point of contention between classical and Bayesian statistics that is brought to the fore when examining so-called ‘persistent experimenters’—the issue of stopping rules, or more accurately, outcome spaces, and their influence on statistical analysis. First, a working definition of classical and Bayesian statistical tests is given, which makes clear that (1) once an experimental outcome is recorded, other possible outcomes matter only for classical inference, and (2) full outcome spaces are nevertheless relevant to both the (...) classical and Bayesian approaches, when it comes to planning/choosing a test. The latter point is shown to have important repercussions. Here we argue that it undermines what Bayesians may admit to be a compelling argument against their approach—the Bayesian indifference to persistent experimenters and their optional stopping rules. We acknowledge the prima facie appeal of the pro-classical ‘optional stopping intuition’, even for those who ordinarily have Bayesian sympathies. The final section of the paper, however, provides three error theories that may assist a Bayesian in explaining away the apparent anomaly in their reasoning. (shrink)

I consider three theses that are friendly to anthropomorphism. Each makes a claim about what can be inferred about the mental life of chimpanzees from the fact that humans and chimpanzees both have behavioral trait B and humans produce this behavior by having mental trait M. The first thesis asserts that this fact makes it probable that chimpanzees have M. The second says that this fact provides strong evidence that chimpanzees have M. The third claims that the fact is evidence (...) that chimpanzees have M. The third thesis follows from a plausible Reichenbachian model of how a common ancestor is probabilistically related to its descendants. The first two theses do not, and they have no general evolutionary justification. (shrink)

This chapter offers a critique of intelligent design arguments against evolution and a philosophical discussion of the nature of science, drawing several lessons for the teaching of evolution and for science education in general. I discuss why Behe’s irreducible complexity argument fails, and why his portrayal of organismal systems as machines is detrimental to biology education and any under-standing of how organismal evolution is possible. The idea that the evolution of complex organismal features is too unlikely to have occurred by (...) random mutation and selection (as recently promoted by Dembski) is very widespread, but it is easy to show students why such small probability arguments are fallacious. While intelligent design proponents have claimed that the exclusion of supernatural causes mandated by scientific methods is dogmatically presupposed by science, scientists have an empirical justification for using such methods. This justification is instructive for my discussion of how to demarcate science from pseudoscience. I argue that there is no universal account of the nature of science, but that the criteria used to judge an intellectual approach vary across historical periods and have to be specific to the scientific domain. Moreover, intellectual approaches have to be construed as practices based on institutional factors and values, and to be evaluated in terms of the activities of their practitioners. Science educators should not just teach scientific facts, but present science as a practice and make students reflect on the nature of science, as this gives them a better appreciation of the ways in which intelligent design falls short of actual science. (shrink)

According to Hitchcock and Sober’s argument from overfitting for weak predictivism, the fact that a theory accurately predicts a portion of its data is evidence that it has been formulated by balancing simplicity and goodness-of-fit rather than overfitting data. The core argument consists of two likelihood inequalities. In this paper I show that there is a surprising accommodation-friendly implication in their argument, and contend that it is beset by a substantial difficulty, namely, there is no good reason to think that (...) their second likelihood inequality is true. (shrink)

The vision of natural kinds that is most common in the modern philosophy of biology, particularly with respect to the question whether species and other taxa are natural kinds, is based on a revision of the notion by Mill in A System of Logic. However, there was another conception that Whewell had previously captured well, which taxonomists have always employed, of kinds as being types that need not have necessary and sufficient characters and properties, or essences. These competing views employ (...) different approaches to scientific methodologies: Mill’s class-kinds are not formed by induction but by deduction, while Whewell’s type-kinds are inductive. More recently, phylogenetic kinds (clades, or monophyletic-kinds) are inductively projectible, and escape Mill’s strictures. Mill’s version represents a shift in the notions of kinds from the biological to the physical sciences. (shrink)

Amalgamating evidence of different kinds for the same hypothesis into an overall confirmation is analogous, I argue, to amalgamating individuals’ preferences into a group preference. The latter faces well-known impossibility theorems, most famously “Arrow’s Theorem”. Once the analogy between amalgamating evidence and amalgamating preferences is tight, it is obvious that amalgamating evidence might face a theorem similar to Arrow’s. I prove that this is so, and end by discussing the plausibility of the axioms required for the theorem.

This (brief) note is about the (evidential) “favoring” relation. Pre-theoretically, favoring is a three-place (epistemic) relation, between an evidential proposition E and two hypotheses H1 and H2. Favoring relations are expressed via locutions of the form: E favors H1 over H2. Strictly speaking, favoring should really be thought of as a four-place relation, between E, H1, H2, and a corpus of background evidence K. But, for present purposes (which won't address issues involving K), I will suppress the background corpus, so (...) as to simplify our discussion. Moreover, the favoring relation is meant to be a propositional epistemic relation, as opposed to a doxastic epistemic relation. That is, the favoring relation is not meant to be restricted to bodies of evidence that are possessed (as evidence) by some actual agent(s), or to hypotheses that are (in fact) entertained by some actual agent(s). In this sense, favoring is analogous to the relation of propositional justification — as opposed to doxastic justification (Conee 1980). In order to facilitate a comparison of Likelihoodist vs Bayesian explications of favoring, I will presuppose the following bridge principle, linking favoring and evidential support: • E favors H1 over H2 iff E supports H1 more strongly than E supports H2.1 Finally, I will only be discussing instances of the favoring relation involving contingent, empirical claims. So, it is to be understood that “favoring” will not apply if any of E, H1, or H2 are non-contingent (and/or non-empirical). With this background in place, we're ready to begin. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These (...) kinds of general and normative questions make philosophical reflection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reflection on a wide range of findings in cognitive science. (shrink)

‘Bayesian epistemology’ became an epistemological movement in the 20th century, though its two main features can be traced back to the eponymous Reverend Thomas Bayes (c. 1701-61). Those two features are: (1) the introduction of a formal apparatus for inductive logic; (2) the introduction of a pragmatic self-defeat test (as illustrated by Dutch Book Arguments) for epistemic rationality as a way of extending the justification of the laws of deductive logic to include a justification for the laws of inductive logic. (...) The formal apparatus itself has two main elements: the use of the laws of probability as coherence constraints on rational degrees of belief (or degrees of confidence) and the introduction of a rule of probabilistic inference, a rule or principle of conditionalization. (shrink)

This overview of philosophy of biology lays out what implications biology and recent philosophy of biology have for general philosophy of science. The following topics are addressed in five sections: natural kinds, conceptual change, discovery and confirmation, explanation and reduction, and naturalism.

A variety of different arguments have been offered for teaching ‘‘both sides’’ of the evolution/ID debate in public schools. This article reviews five of the most common types of arguments advanced by proponents of Intelligent Design and demonstrates how and why they are founded on confusion and misunderstanding. It argues on behalf of teaching evolution, and relegating discussion of ID to philosophy or history courses.

Evolutionary biology is a field currently animated by much discussion concerning its conceptual foundations. On the one hand, we have supporters of a classical view of evolutionary theory, whose backbone is provided by population genetics and the so-called Modern Synthesis (MS). On the other hand, a number of researchers are calling for an Extended Synthe- sis (ES) that takes seriously both the limitations of the MS (such as its inability to incorporate developmental biology) and recent empirical and theoretical research on (...) issues such as evolvability, modularity, and self-organization. In this article, I engage in an in-depth commentary of an influential paper by population geneticist Michael Lynch, which I take to be the best defense of the MS-population genetics position published so far. I show why I think that Lynch’s arguments are wanting and propose a modification of evolutionary theory that retains but greatly expands on population genetics. (shrink)

In recent controversies about Intelligent Design Creationism (IDC), the principle of methodological naturalism (MN) has played an important role. In this paper, an often neglected distinction is made between two different conceptions of MN, each with its respective rationale and with a different view on the proper role of MN in science. According to one popular conception, MN is a self-imposed or intrinsic limitation of science, which means that science is simply not equipped to deal with claims of the supernatural (...) (Intrinsic MN or IMN). Alternatively, we will defend MN as a provisory and empirically grounded attitude of scientists, which is justified in virtue of the consistent success of naturalistic explanations and the lack of success of supernatural explanations in the history of science (Provisory MN or PMN). Science does have a bearing on supernatural hypotheses, and its verdict is uniformly negative. We will discuss five arguments that have been proposed in support of IMN: the argument from the definition of science, the argument from lawful regularity, the science stopper argument, the argument from procedural necessity, and the testability argument. We conclude that IMN, because of its philosophical flaws, proves to be an ill-advised strategy to counter the claims of IDC. Evolutionary scientists are on firmer ground if they discard supernatural explanations on purely evidential grounds, instead of ruling them out by philosophical fiat. (shrink)

The chapter discusses the principle of conservatism and traces how the general principle is related to the specific one. This tracing suggests that the principle of conservatism needs to be refined. Connecting the principle in cognitive science to more general questions about scientific inference also allows us to revisit the question of realism versus instrumentalism. The framework deployed in model selection theory is very general; it is not specific to the subject matter of science. The chapter outlines some non-Bayesian ideas (...) that have been developed in model selection theory. The principle of conservatism, like C. Lloyd Morgan's canon, describes a preference concerning kinds of parameters. It says that a model that postulates only lower-level intentionality is preferable to one that postulates higher-level intentionality if both fit the data equally well. The model selection approach to parsimony helps explain why unification is a theoretical virtue. (shrink)

While epistemic justification is a central concern for both contemporary epistemology and philosophy of science, debates in contemporary epistemology about the nature of epistemic justification have not been discussed extensively by philosophers of science. As a step toward a coherent account of scientific justification that is informed by, and sheds light on, justificatory practices in the sciences, this paper examines one of these debates—the internalist-externalist debate—from the perspective of objective accounts of scientific evidence. In particular, we focus on Deborah Mayo’s (...) error-statistical theory of evidence because it is a paradigmatically objective theory of evidence that is strongly informed by methodological practice. We contend that from the standpoint of such an objective theory of evidence, justification in science has both externalist and internalist characteristics. In reaching this conclusion, however, we find that the terms of the contemporary debate between internalists and externalists have to be redefined to be applicable to scientific contexts. (shrink)

While the common procedure of statistical significance testing and its accompanying concept of p-values have long been surrounded by controversy, renewed concern has been triggered by the replication crisis in science. Many blame statistical significance tests themselves, and some regard them as sufficiently damaging to scientific practice as to warrant being abandoned. We take a contrary position, arguing that the central criticisms arise from misunderstanding and misusing the statistical tools, and that in fact the purported remedies themselves risk damaging science. (...) We argue that banning the use of p-value thresholds in interpreting data does not diminish but rather exacerbates data-dredging and biasing selection effects. If an account cannot specify outcomes that will not be allowed to count as evidence for a claim—if all thresholds are abandoned—then there is no test of that claim. The contributions of this paper are: To explain the rival statistical philosophies underlying the ongoing controversy; To elucidate and reinterpret statistical significance tests, and explain how this reinterpretation ameliorates common misuses and misinterpretations; To argue why recent recommendations to replace, abandon, or retire statistical significance undermine a central function of statistics in science: to test whether observed patterns in the data are genuine or due to background variability. (shrink)

Lucas Matthews and I substantially revised my SEP entry on Heritability. This version includes discussion of the missing heritability problem and other issues that arise from the use of Genome Wide Association Studies by Behavioral Geneticists.

There is an active research program currently underway, which treats cancer progression as an evolutionary process. This contribution investigates the ways that cancer progression is like and unlike evolution in other contexts. The aim is to take a multi-level perspective on cancer, investigating the levels at which selection may be acting, the unit or target of selection, the relative roles of selection and drift, and the idea that cancer progression may be a by-product of selection at other levels of organization.

Classical statistical inferences have been criticised for various reasons. To assess the soundness of such criticisms is a very important task because they are widely used in everyday scientific research. This is one of the reasons why the philosophy of statistics is an exciting field of study. In this paper, I focus on two such criticisms. The first one claims that the use of the p-value violates the principle of total evidence. It is a thesis that has been defended by (...) Elliott Sober and Bengt Autzen. The second one says that the result of classical tests does not only depend on the data but on the sampling plan of the experimenter also. The underlying criticism of course is that the sampling plan is not part of the evidence and that classical tests therefore violate PTE. The intentions of the experimenter should not affect the result of an inference. My aim is to show that both criticisms are unsound. Doing so, I hope to clarify the concept of p-value and the nature of the evidence in classical statistical tests. The point of my paper is to show that the identification of the evidence on which those criticisms rest is inadequate. (shrink)

Even if two testimonies in a criminal trial are independent, they are not necessarily more trustworthy than one. But if they are independent in the sense that they are screened off from one another by the crime, then two testimonies raise the probability of guilt above the level that one testimony alone could achieve. In fact this screening-off condition can be weakened without changing the conclusion. It is however only a sufficient, not a necessary condition for concluding that two witnesses (...) are better than one. We will discuss two different conditions, each of them necessary as well as sufficient, and we conclude that one of them is slightly better than the other. (shrink)

What does it mean for a hypothesis to be ad hoc? One prominent account has it that ad hoc hypotheses have no independent empirical support. Others have viewed ad hoc judgements as subjective. Here I critically review both of these views and defend my own Coherentist Conception of Ad hocness by working out its conceptual and descriptive attractions.

The teaching of evolution in American high schools has long been a source of controversy. The past decade has seen an important shift in the rhetoric of anti-evolutionists, toward arguments of a strongly mathematical character. These mathematical arguments, while different in their specifics, follow the same general program and rely on the same underlying model of evolution. We shall discuss the nature and history of this program and model and describe general reasons for skepticism with regard to any anti-evolutionary arguments (...) based upon them. We shall then survey the major arguments used by anti-evolutionists, to show how our general considerations make it possible to quickly identify their weakest points. (shrink)

In this paper we consider the problem of how to measure the strength of statistical evidence from the perspective of evidence amalgamation operations. We begin with a fundamental measurement amalgamation principle : for any measurement, the inputs and outputs of an amalgamation procedure must be on the same scale, and this scale must have a meaningful interpretation vis a vis the object of measurement. Using the p value as a candidate evidence measure, we examine various commonly used approaches to amalgamation (...) of evidence across similar studies, including standard forms of meta-analysis. We show that none of these methods satisfies MAP. Thus an underlying measurement problem remains. We argue that a successful approach to evidence amalgamation necessitates a solution to the problem of evidence measurement, and we suggest some lines of reasoning that might guide further work towards this end. (shrink)

We are fallible, and knowledge of our fallibility has normative implications. But these normative implications appear to conflict with other compelling epistemic norms. We therefore appear to face a choice: reject fallibility-based norms or reject these other epistemic norms. I argue that there is a plausible third option: reconcile these two sets of norms. Once we properly understand the nature of each of these norms, we aren’t forced to reject either.

I aim to provide some evidence that Husserl’s description of perceptual updating actually fits very nicely into the Bayesian Brain paradigm, articulated by Karl Friston and others, and that that paradigm, in turn, can be taken as an excellent example of “Neurophenomenology”. The apparently un-phenomenological Helmholtzian component of the Bayesian Brain paradigm, according to which what one consciously seems to see is a product of unconscious causal reasoning to the best explanation of one’s sensory stimulations, can be finessed, I claim, (...) in a way that makes it compatible with a phenomenological orientation. I begin by roughly characterizing the Bayesian Brain paradigm as it relates to perceptual cognition. I then show how Husserl’s descriptions of the conscious perceptual process relate to the paradigm. I conclude with some considerations about how to understand the relation between conscious and unconscious brain process in the present case and in relation to Neurophenomenology generally. (shrink)

Current empirical studies of moral behavior of healthcare professionals are almost entirely focused on self-reports, usually collected under the assumption that an ethical disposition characterizes individuals across various contexts. It is well known, however, that individuals adjust their behavior to what they see being done by those in their peer group. That presents a methodological challenge to traditional research within a community of peers because the behavior of each individual is both the result of norms and a contributor to the (...) norms of others. Computer simulations can be used to address this methodological challenge. A Markov replicator model that runs on an Excel spreadsheet was used to investigate a community with four agent types in the dental community: devious practitioners, ethical practitioners who avoid involvement in the poor ethics of others, ethical practitioners who accept it as part of their professional responsibility to challenge colleagues who act unprofessionally, and those who enforce ethical standards. A panel of leaders in the profession independently estimated parameters for the model and criteria for a possible distribution of agent types in the community. The simulation converged on distributions of the agent types that were very similar to the expectations of the panel. The simulation suggests the following characteristics of such moral communities: The structure of such communities is robust across a wide distribution. It appears that reduction in unethical behavior is more sensitive to the way ethical practitioners interact with each other than to sanctions the enforcement community imposes on unethical practitioners, and that large external interventions will be short lived. (shrink)

Both Aristotle and Ernst Mayr present theories of dual explanation in biology, with proximal, clearly physical explanations and more distal, biology-specific explanations. Aristotle’s presentation of final cause explanations in Posterior Analytics relates final causes to the necessary material, formal, and efficient causes that mediate them. Johnson and Leunissen demonstrate the problematic nature of historical and recent interpretations and open the door for a new interpretation consistent with modern evolutionary theory. Mayr’s differentiation of proximate and ultimate/evolutionary causes provides a key to (...) appropriating Aristotle for modern use, if care is taken to differentiate Mayr’s proximate/distal and mechanical/evolutionary distinctions from his intentional/non-intentional distinction. Building on Mayr, and noting his appropriation of ancient and recent commentary, a strong case can be made for nested explanation, wherein evolutionary explanations are instantiated in systems of mechanical explanations. Biological concepts of organism, gene, function, etc., are etiologically prior to mechanical explanations of function, but temporally posterior to mechanical explanations of historical adaptation. Such an analysis sheds light on recent arguments within evolutionary biology while highlighting the importance of epistemology in contemporary science. (shrink)

A dominant view in contemporary cognitive neuroscience is that low-level, comparator-based mechanisms of motor control produce a distinctive experience often called the feeling of agency . An opposing view is that comparator-based motor control is largely non-conscious and not associated with any particular type of distinctive phenomenology . In this paper, I critically evaluate the nature of the empirical evidence researchers commonly take to support FoA-hypothesis. The aim of this paper is not only to scrutinize the FoA-hypothesis and data supposed (...) to support it; it is equally to argue that experimentalists supporting the FoA-hypothesis fail to establish that the experimental outcomes are more probable given the FoA-hypothesis than given the simpler hypothesis. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

We examine the claim that the methodology of psychology leads to a bias in animal cognition research against attributing “anthropomorphic” properties to animals . This charge is examined in light of a debate on the role of folk psychology between primatologists who emphasize similarities between humans and other apes, and those who emphasize differences. We argue that while in practice there is sometimes bias, either in the formulation of the null hypothesis or in the preference of Type-II errors over Type-I (...) errors, the bias is not the result of proper use of the Neyman and Pearson hypothesis testing method. Psychologists’ preference for false negatives over false positives cannot justify a preference for avoiding anthropomorphic errors over anthropectic errors. (shrink)

Richard Boyd and Nicholas Sturgeon develop distinctive naturalistic arguments for scientific realism and moral realism. Each defends a realist position by an inference to the best explanation. In this paper, I suggest that these arguments for realism should be reformulated, with the law of likelihood replacing inference to the best explanation. The resulting arguments for realism do not work.

Phylogenetic trees are meant to represent the genealogical history of life and apparently derive their justification from the existence of the tree of life and the fact that evolutionary processes are treelike. However, there are a number of problems for these assumptions. Here it is argued that once we understand the important role that phylogenetic trees play as models that contain idealizations, we can accept these criticisms and deny the reality of the tree while justifying the continued use of trees (...) in phylogenetic theory and preserving nearly all of what defenders of trees have called the “importance of tree thinking.”. (shrink)

I believe that tenured historians, philosophers, and sociologists of science—when presented with the opportunity—have a professional obligation to get involved in public controversies over what should count as science. I stress ‘tenured’ because the involved academics need to be materially protected from the consequences of their involvement, given the amount of misrepresentation and abuse that is likely to follow, whatever position they take. Indeed, the institution of academic tenure justifies itself most clearly in such heat-seeking situations, where one may appear (...) to offer a reasoned defense for views that many consider indefensible. To be sure, the opportunities for involvement will vary in kind and number, but I believe that we are obliged to embrace them. In the specific case of ‘demarcation’ questions of what counts as science, the people who possess the sort of general and comparative knowledge most relevant for adducing this matter are historians, philosophers, and sociologists of science—not professional scientists unschooled in these areas.. (shrink)

Markov models of evolution describe changes in the probability distribution of the trait values a population might exhibit. In consequence, they also describe how entropy and conditional entropy values evolve, and how the mutual information that characterizes the relation between an earlier and a later moment in a lineage’s history depends on how much time separates them. These models therefore provide an interesting perspective on questions that usually are considered in the foundations of physics—when and why does entropy increase and (...) at what rates do changes in entropy take place? They also throw light on an important epistemological question: are there limits on what your observations of the present can tell you about the evolutionary past? (shrink)

The sheer multitude of criteria of empirical significance has been taken as evidence that the pre-analytic notion being explicated is too vague to be useful. I show instead that a significant number of these criteria—by Ayer, Popper, Przełęcki, Suppes, and David Lewis, among others—not only form a coherent whole, but also connect directly to the theory of definition, the notion of empirical content as explicated by Ramsey sentences, and the theory of measurement; two criteria by Carnap and Sober are trivial, (...) but can be saved and connected to the other criteria by slight modifications. A corollary is that the ordinary language defense of Lewis, the conceptual arguments by Ayer and Popper, the theoretical considerations by Przełęcki, and the practical considerations by Suppes all apply to the same criterion or closely related criteria. Furthermore, the equivalence of some criteria allows for their individual justifications to be taken cumulatively and, together with the entailment relations between nonequivalent criteria, suggest criteria for general auxiliary assumptions, comparative criteria, and more liberal conceptions of observation. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

It can often be heard in the hallways, and occasionally read in print, that reliabilism runs into special trouble regarding lottery cases. My main aim in this paper is to argue that this is not so. Nevertheless, lottery cases do force us to pay close attention to the relation between justification and probability.

The dangers of character reification for cladistic inference are explored. The identification and analysis of characters always involves theory-laden abstraction—there is no theory-free “view from nowhere.” Given theory-ladenness, and given a real world with actual objects and processes, how can we separate robustly real biological characters from uncritically reified characters? One way to avoid reification is through the employment of objectivity criteria that give us good methods for identifying robust primary homology statements. I identify six such criteria and explore each (...) with examples. Ultimately, it is important to minimize character reification, because poor character analysis leads to dismal cladograms, even when proper phylogenetic analysis is employed. Given the deep and systemic problems associated with character reification, it is ironic that philosophers have focused almost entirely on phylogenetic analysis and neglected character analysis. (shrink)

Inductive reasoning aims at constructing rules and models of general applicability from a restricted set of observations. Induction is a keystone in natural sciences, and it influences diverse application fields such as engineering, medicine and economics. More generally, induction plays a major role in the way humans learn and operate in their everyday life. The level of reliability that a model achieves depends on how informative the observations are relative to the flexibility of the process by which the model is (...) constructed. When the process is articulated so that the model can incorporate descriptive details and subtleties, a large set of informative observations are required to reliably tune the model, whereas models obtained from simple procedures can be tuned with fewer observations. This article introduces the concept of “dominance”, which refers to the situation in which a reduced subset of observations suffices to reconstruct the model. A mathematical framework is presented to quantify the reliability of learning procedures as a function of the size of the subset of dominant observations. Although limited in scope, we believe that our study can contribute to the understanding of some fundamental mechanisms by which knowledge is generated from observations in inductive reasoning. (shrink)