Recent discussion of the statistical character of evolutionary theory has centered around two positions: Determinism combined with the claim that the statistical character is eliminable, a subjective interpretation of probability, and instrumentalism; Indeterminism combined with the claim that the statistical character is ineliminable, a propensity interpretation of probability, and realism. I point out some internal problems in these positions and show that the relationship between determinism, eliminability, realism, and the interpretation of probability is more complex than previously assumed in this (...) debate. Furthermore, I take some initial steps towards a more adequate account of the statistical character of evolutionary theory. (shrink)

Former discussions of biological generalizations have focused on the question of whether there are universal laws of biology. These discussions typically analyzed generalizations out of their investigative and explanatory contexts and concluded that whatever biological generalizations are, they are not universal laws. The aim of this paper is to explain what biological generalizations are by shifting attention towards the contexts in which they are drawn. I argue that within the context of any particular biological explanation or investigation, biologists employ two (...) types of generations. One type identifies causal regularities exhibited by particular kinds of biological entities. The other type identifies how these entities are distributed in the biological world. (shrink)

According to Aristotelian essentialism, the nature of an organism is constituted of a particular goal-directed disposition to produce an organism typical of its kind. This paper argues—against the prevailing orthodoxy—that essentialism of this sort is indispensable to evolutionary biology. The most powerful anti-essentialist arguments purport to show that the natures of organisms play no explanatory role in modern synthesis biology. I argue that recent evolutionary developmental biology provides compelling evidence to the contrary. Developmental biology shows that one must appeal to (...) the capacities of organisms to explain what makes adaptive evolution adaptive. Moreover, the specific capacities in question are precisely those that, according to Aristotle, constitute the nature of an organism. Essentialism 1.1 Aristotelian biological kinds Evolutionary anti-essentialism 2.1 Taxonomic anti-essentialism 2.2 Explanatory anti-essentialism Adaptation 3.1 Stability 3.2 Mutability 3.3 Phenotypic plasticity and adaptive evolution The natures of organisms Conclusion. (shrink)

Suppe, F. The search for philosophic understanding of scientific theories (p. [1]-241)--Proceedings of the symposium.--Bibliography, compiled by Rew A. Godow, Jr. (p. [615]-646).

The positivistic Received View construed scientific theories syntactically as axiomatic calculi where theoretical terms were given a partial semantic interpretation via correspondence rules connecting them to observation statements. This paper assesses what, with hindsight, seem the most important defects in the Received View; surveys the main proposed successor analyses to the Received View--various Semantic Conception versions and the Structuralist Analysis; evaluates how well they avoid those defects; examines what new problems they face and where the most promising require further development (...) or leave unanswered questions; explores implications of recent work on models for understanding theories; and rebuts the few criticisms of the Semantic Conception that have surfaced. (shrink)

According to principles of probability coordination, such as Miller's Principle or Lewis's Principal Principle, you ought to set your subjective probability for an event equal to what you take to be the objective probability of the event. For example, you should expect events with a very high probability to occur and those with a very low probability not to occur. This paper examines the grounds of such principles. It is argued that any attempt to justify a principle of probability coordination (...) encounters the same difficulties as attempts to justify induction. As a result, no justification can be found. (shrink)

The present paper studies a specific way of addressing the question whether the laws involving the basic constituents of nature are statistical. While most German physicists, above all Planck, treated the issues of determinism and causality within a Kantian framework, the tradition which I call Vienna Indeterminism began from Mach’s reinterpretation of causality as functional dependence. This severed the bond between causality and realism because one could no longer avail oneself of a priori categories as a criterion for empirical reality. (...) Hence, an independent reality criterion had to be sought, a problem which all three physicists to be studied solved in different ways that were mainly conditioned by their different concepts of probability. In order to prevent a dissipation of intuited facts, Mach had to resort to a principle of unique determination as his reality criterion, especially when discussing the Principle of Least Action. Giving theories more independence, Boltzmann understood atomism as property reduction to precisely defined theoretical entities and their interactions. While this served as a relative reality criterion, he also advocated a constructivist one because atomism was already implied by our finitary reasoning power. Finally, Exner contemplated the idea that all apparently deterministic laws are only a macroscopic limit of an irreducible indeterminism, because by adopting the frequency interpretation, observable collectives could be considered as the real basic entities. (shrink)

Critics of the ideal of value‐free science often assume that they must reject the distinction between epistemic and nonepistemic values. I argue that this assumption is mistaken and that the distinction can be used to clarify and defend the argument from inductive risk, which challenges the value‐free ideal. I develop the idea that the characteristic feature of epistemic values is that they promote, either intrinsically or extrinsically, the attainment of truths. This proposal is shown to answer common objections to the (...) distinction and provide a principled basis for separating legitimate from illegitimate influences of nonepistemic values in scientific inference. *Received June 2009; revised September 2009. †To contact the author, please write to: 503 S. Kedzie Hall, Michigan State University, East Lansing, MI 48824‐1032; e‐mail: [email protected]. (shrink)

This paper is structured around the three elements of the title. Section 2 claims that (a) structures need objects and (b) scientific structuralism should focus on in re structures. Therefore, pure structuralism is undermined. Section 3 discusses whether the world has `excess structure' over the structure of appearances. The main point is that the claim that only structure can be known is false. Finally, Section 4 argues directly against ontic structural realism that it lacks the resources to accommodate causation within (...) its structuralist slogan. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring "goodness" of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of.5 occur, 70 percent of forecasts made with probability.7 occur, etc. To summarize the conclusions: (i) Surveys designed to display calibration curves, from which a (...) recalibration is to be calculated, are useless without due consideration for the interconnections between questions (forecasts) in the survey. (ii) Subject to feedback, calibration in the long run is otiose. It gives no ground for validating one coherent opinion over another as each coherent forecaster is (almost) sure of his own long-run calibration. (iii) Calibration in the short run is an inducement to hedge forecasts. A calibration score, in the short run, is improper. It gives the forecaster reason to feign violation of total evidence by enticing him to use the more predictable frequencies in a larger finite reference class than that directly relevant. (shrink)

Leslie Graves, Barbara Horan and Alex Rosenberg (1999) have argued that the process of evolution is really deterministic, so we should be instrumentalists about our probabilistic evolutionary theory. I criticize the consistency of their view. I argue that because they are realists towards multiple theories (quantum mechanics and macrophysics) their arguments against realism for another scientific theory fail. The main point of this paper is critical, but in order to set up this criticism I explore the ramifications of realism for (...) multiple theories. Finally, I offer a brief metaphysical justification for realism about multiple theories. This view justifies realism for evolutionary theory, which has been defended by Robert Brandon and Scott Carson (1996). (shrink)

The question of the relationship of the making of value judgments in a typically ethical sense to the methods and procedures of science has been discussed in the literature at least to that point which e. e. cummings somewhere refers to as “The Mystical Moment of Dullness.” Nevertheless, albeit with some trepidation, I feel that something more may fruitfully be said on the subject.

In this paper it is argued that qualitative theories (Q-theories) can be used to describe the statistical structure of cross classified populations and that the notion of verisimilitude provides an appropriate tool for measuring the statistical adequacy of Q-theories. First of all, a short outline of the post-Popperian approaches to verisimilitude and of the related verisimilitudinarian non-falsificationist methodologies (VNF-methodologies) is given. Secondly, the notion of Q-theory is explicated, and the qualitative verisimilitude of Q-theories is defined. Afterwards, appropriate measures for the (...) statistical verisimilitude of Q-theories are introduced, so to obtain a clear formulation of the intuitive idea that the statistical truth about cross classified populations can be approached by falsified Q-theories. Finally, it is argued that some basic intuitions underlying VNF-methodologies are shared by the so-called prediction logic, developed by the statisticians and social scientists David K. Hildebrand, James D. Laing and Howard Rosenthal. (shrink)

We present a precise form of structural realism, called group structural realism , which identifies ‘structure’ in quantum theory with symmetry groups. However, working out the details of this view actually illuminates a major problem for structural realism; namely, a structure can itself have structure. This article argues that, once a precise characterization of structure is given, the ‘metaphysical hierarchy’ on which group structural realism rests is overly extravagant and ultimately unmotivated.

The architects of the modern synthesis banned essentialism from evolutionary theory. This rejection of essentialism was motivated by Darwin’s theory of natural selection, and the continuity of evolutionary transformation. Contemporary evolutionary biology witnesses a renaissance of essentialism in three contexts: “origin essentialism” with respect to species and supraspecific taxa, the bar coding of species on the basis of discontinuities of DNA variation between populations, and the search for laws of evolutionary developmental biology. Such “new essentialism” in contemporary biology must be (...) of a new kind that accommodates relational (extrinsic) properties as historical essences and cluster concepts of natural kinds. (shrink)

According to a recent suggestion, the names of gene taxa should be conceived of as referring to individuals with concrete genes as their parts, just as the names of biological species are often understood as denoting individuals with organisms as their parts. Although prima facie this suggestion might advance the debate on gene concepts in a similar way as the species-are-individuals thesis advanced the debate on species concepts, I argue that the principal arguments in support of the gene-individuality thesis are (...) much less compelling than the parallel arguments in the species case. In addition, I argue that the notion of biological function invoked in the gene-individuality thesis (selected effect) is not the one that biologists actually use when individuating genes. Contra the gene-individuality thesis, I argue that gene names refer to kinds, defined primarily (though not exclusively) by causal-role functions. (shrink)

Species in biology are traditionally perceived as kinds of organisms about which explanatory and predictive generalizations can be made, and biologists commonly use species in this manner. This perception of species is, however, in stark contrast with the currently accepted view that species are not kinds or classes at all, but individuals. In this paper I investigate the conditions under which the two views of species might be held simultaneously. Specifically, I ask whether upon acceptance of an ontology of species (...) as diachronic segments of the tree of life species can perform the epistemic role of kinds of organisms to which explanatory and predictive generalizations apply. I show that, for species-level segments of the tree of life, several requirements have to be met before the performance of this epistemic role is possible, and I argue that these requirements can be met by defining species according to the Composite Species Concept proposed by Kornet and McAllister in the 1990s. (shrink)

Biologists and philosophers of biology typically regard essentialism about speciesas incompatible with modern Darwinian theory. Analytic metaphysicians such asKripke, Putnam and Wiggins, on the other hand, believe that their essentialist thesesare applicable to biological kinds. I explore this tension. I show that standard anti-essentialist considerations only show that species do not have intrinsic essential properties. I argue that while Putnam and Kripke do make assumptions that contradict received biological opinion, their model of natural kinds, suitably modified, is partially applicable to (...) biological species. However, Wiggins'' thesis that organisms belong essentially to their species is untenable, given modern species concepts. I suggest that Putnam''s, Kripke''s and Wiggins'' errors stem from adopting an account of the point of scientific classification which implies that relationally-defined kinds are likely to be of little value, an account which is inapplicable to biology. (shrink)

What does it take for one proposition to be closer to the truth than another. In this, the first published monograph on the topic, Oddie develops a comprehensive theory that takes the likeness in truthlikeness seriously.

Popper distinguishes the problems of theoretical and pragmatic preference between rival theories, but he claims that there is a common non-inductive solution to both of them, viz. the "best-tested theory", or the theory with the highest degree of corroboration. He further suggests that the degrees of corroboration serve as indicators of verisimilitude. One may therefore raise the question whether the recent theory of verisimilitude gives a general non-inductive solution to the problem of theoretical preference. This paper argues that this is (...) not the case: the theory of verisimilitude is applicable to this problem if and only if there is an independent solution to the problem of induction. Moreover, the solutions to the theoretical and pragmatic problems of preference coincide only in some special cases. (shrink)

The distinction between basic and applied research is notoriously vague, despite its frequent use in science studies and in science policy. In most cases it is based on such pragmatic factors as the knowledge and intentions of the investigator or the type of research institute. Sometimes the validity of the distinction is denied altogether. This paper suggests that there are two ways of distinguishing systematically between basic and applied research: (i) in terms of the utilities that define the aims of (...) inquiry, and (ii) by reference to the structure of the relevant knowledge claims. An important type of applied research aims at results that are expressed by techical norms (in von Wright's sense): if you wish to achieveA, and you believe you are in a situationB, then you should doX. This conception of design sciences allows us to re-evaluate many issues in the history, philosophy, and ethics of science. (shrink)

Beatty, Brandon, and Sober agree that biological generalizations, when contingent, do not qualify as laws. Their conclusion follows from a normative definition of law inherited from the Logical Empiricists. I suggest two additional approaches: paradigmatic and pragmatic. Only the pragmatic represents varying kinds and degrees of contingency and exposes the multiple relationships found among scientific generalizations. It emphasizes the function of laws in grounding expectation and promotes the evaluation of generalizations along continua of ontological and representational parameters. Stability of conditions (...) and strength of determination in nature govern projectibility. Accuracy, ontological level, simplicity, and manageability provide additional measures of usefulness. (shrink)

Evolutionary theory (ET) is teeming with probabilities. Probabilities exist at all levels: the level of mutation, the level of microevolution, and the level of macroevolution. This uncontroversial claim raises a number of contentious issues. For example, is the evolutionary process (as opposed to the theory) indeterministic, or is it deterministic? Philosophers of biology have taken different sides on this issue. Millstein (1997) has argued that we are not currently able answer this question, and that even scientific realists ought to remain (...) agnostic concerning the determinism or indeterminism of evolutionary processes. If this argument is correct, it suggests that, whatever we take probabilities in ET to be, they must be consistent with either determinism or indeterminism. This raises some interesting philosophical questions: How should we understand the probabilities used in ET? In other words, what is meant by saying that a certain evolutionary change is more or less probable? Which interpretation of probability is the most appropriate for ET? I argue that the probabilities used in ET are objective in a realist sense, if not in an indeterministic sense. Furthermore, there are a number of interpretations of probability that are objective and would be consistent with ET under determinism or indeterminism. However, I argue that evolutionary probabilities are best understood as propensities of population-level kinds. (shrink)

Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error probabilities (...) is to ensure that only statistical hypotheses that have passed severe or probative tests are inferred from the data. The severity criterion supplies a meta-statistical principle for evaluating proposed statistical inferences, avoiding classic fallacies from tests that are overly sensitive, as well as those not sensitive enough to particular errors and discrepancies. Introduction and overview 1.1 Behavioristic and inferential rationales for Neyman–Pearson (N–P) tests 1.2 Severity rationale: induction as severe testing 1.3 Severity as a meta-statistical concept: three required restrictions on the N–P paradigm Error statistical tests from the severity perspective 2.1 N–P test T(): type I, II error probabilities and power 2.2 Specifying test T() using p-values Neyman's post-data use of power 3.1 Neyman: does failure to reject H warrant confirming H? Severe testing as a basic concept for an adequate post-data inference 4.1 The severity interpretation of acceptance (SIA) for test T() 4.2 The fallacy of acceptance (i.e., an insignificant difference): Ms Rosy 4.3 Severity and power Fallacy of rejection: statistical vs. substantive significance 5.1 Taking a rejection of H0 as evidence for a substantive claim or theory 5.2 A statistically significant difference from H0 may fail to indicate a substantively important magnitude 5.3 Principle for the severity interpretation of a rejection (SIR) 5.4 Comparing significant results with different sample sizes in T(): large n problem 5.5 General testing rules for T(), using the severe testing concept The severe testing concept and confidence intervals 6.1 Dualities between one and two-sided intervals and tests 6.2 Avoiding shortcomings of confidence intervals Beyond the N–P paradigm: pure significance, and misspecification tests Concluding comments: have we shown severity to be a basic concept in a N–P philosophy of induction? (shrink)

Probability theory is important not least because of its relevance for decision making, which also means: its relevance for the single case. The frequency theory of probability on its own is irrelevant in the single case. However, Howson and Urbach argue that Bayesianism can solve the frequentist's problem: frequentist-probability information is relevant to Bayesians. The present paper shows that Howson and Urbach's solution cannot work, and indeed that no Bayesian solution can work. There is no way to make frequentist probability (...) relevant. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

After decades of neglect philosophers of physics have discovered gauge theories--arguably the paradigm of modern field physics--as a genuine topic for foundational and philosophical research. Incidentally, in the last couple of years interest from the philosophy of physics in structural realism--in the eyes of its proponents the best suited realist position towards modern physics--has also raised. This paper tries to connect both topics and aims to show that structural realism gains further credence from an ontological analysis of gauge theories--in particular (...) U(1) gauge theory. In the first part of the paper the framework of fiber bundle gauge theories is briefly presented and the interpretation of local gauge symmetry will be examined. In the second part, an ontological underdetermination of gauge theories is carved out by considering the various kinds of non-locality involved in such typical effects as the Aharonov-Bohm effect. The analysis shows that the peculiar form of non-separability figuring in gauge theories is a variant of spatiotemporal holism and can be distinguished from quantum theoretic holism. In the last part of the paper the arguments for a gauge theoretic support of structural realism are laid out and discussed. (shrink)

Structural realism is sometimes said to undermine the theory underdetermination (TUD) argument against realism, since, in usual TUD scenarios, the supposed underdetermination concerns the object-like theoretical content but not the structural content. The paper explores the possibility of structural TUD by considering some special cases from modern physics, but also questions the validity of the TUD argument itself. The upshot is that cases of structural TUD cannot be excluded, but that TUD is perhaps not such a terribly serious anti-realistic argument.

How do we go about weighing evidence, testing hypotheses, and making inferences? The model of " inference to the best explanation " -- that we infer the hypothesis that would, if correct, provide the best explanation of the available evidence--offers a compelling account of inferences both in science and in ordinary life. Widely cited by epistemologists and philosophers of science, IBE has nonetheless remained little more than a slogan. Now this influential work has been thoroughly revised and updated, and features (...) a new introduction and two new chapters. Inference to the Best Explanation is an unrivaled exposition of a theory of particular interest in the fields both of epistemology and the philosophy of science. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)