Analysis of two key ways of characterizing genes—as causes of phenotypic effects and as genomic DNA sequences—has yielded widespread pessimism that they can be united in a coherent gene concept. This raises important questions about the epistemology of genomic research: If analysis of a genome sequence cannot yield information about genes defined both in terms of their products and their DNA sequence, then what could we learn from it? I investigate basic tools of genomic analysis, argue that they do not reflect the application of either gene concept, and clarify how we learn from genomic research.

Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent modeling-based accounts still perpetuate a theory-centric view of scientific concepts, which motivated philosophers’ misplaced skepticism in the first place.

Reverse engineering is a matter of inferring adaptive function from structure. The utility of reverse engineering for evolutionary biology has been a matter of controversy. I offer a simple taxonomy of the uses of engineering design in assessing adaptation, with a variety of illustrations. The plausibility of applications of engineering design reflects the specific way the models are elaborated and derived.

Signature-based model-independent (SBMI) searches for new physics form an explorative component of High Energy Physics experiments that aims at avoiding biases toward beyond-the-standard-model theories. In order to maximize their chances of meeting their objectives, however, SBMI searches must be guided by theory about the target phenomena. They correspond to strategy-driven experiments as defined by Koray Karaca, in contrast to Friedrich Steinle’s conception of explorative experiments. A concept of type II safeness is proposed to explain how the objectives of the experiment introduce theory dependence in the search strategy. Empirical evidence obtained from Large Hadron Collider experiments can therefore not avoid dependence on theory.

This article will explore whether there are arguments for Aristotle's concept mixis which can aid our current discussions within the philosophy of chemistry. We remain troubled by the way and extent to which chemical substance in bulk can be identified with or reduced to the stability and structure of molecules, and whether these in turn can be identified with or reduced to elemental atoms and the quantum theoretical characterization of their electrons. Aristotle was as determined as we are to think through the implications of substances comprised of constituents and to question their status in chemical compounds.

This paper is partly a tribute to Richard Jeffrey, partly a reflection on some of his writings, The Logic of Decision in particular. I begin with a brief biography and some fond reminiscences of Dick. I turn to some of the key tenets of his version of Bayesianism. All of these tenets are deployed in my discussion of his response to the St. Petersburg paradox, a notorious problem for decision theory that involves a game of infinite expectation. Prompted by that paradox, I conclude with some suggestions of avenues for future research.

In a recent book, Laudan has put forward a new and provocative theory of scientific progress. In this discussion we shall show that some of the claims which Laudan presents as new, are (or at least can be made into) parts of more “traditional” wisdom. In particular (in Section 1) we shall criticize his claim to have uncovered a new class of non-refuting anomalies for theories. We shall also (in section 2) criticize Laudan's view that a theory may have an anomaly because of conflict with non-scientific theories—as long as those theories are perceived of as rational. Laudan's view of theory-assessment—via the assessment of “research traditions”—is also examined in this section. It is found to be a significant departure from both traditional, and more radical (Lakatosian, Kuhnian, Feyerabendian) alternatives. Finally, (in Section 3), we examine Laudan's claim that theories may have anomalies because of conflict with methodological theories.

Proponents of individual-based modeling in ecology claim that their models explain the emergence of population-level behavior. This article argues that individual-based models have not, as yet, provided such explanations. Instead, individual-based models can and do demonstrate and explain the emergence of population-level behaviors from individual behaviors and interactions.

James developed an evolutionary objection to epiphenomenalism that is still discussed today. Epiphenomenalists have offered responses that do not grasp its full depth. I thus offer a new reading and assessment of James’s objection. Our life-essential, phenomenal pleasures and pains have three features that suggest that they were shaped by selection, according to James: they are natively patterned, those patterns are systematically linked with antecedent brain states, and the patterns are “universal” among humans. If epiphenomenalism were true, phenomenal patterns could not have been selected (because epiphenomenalism precludes phenomenal consciousness affecting reproductive success). So epiphenomenalism is likely false.

We argue that many recent philosophical discussions about the reference of everyday concepts of intentional states have implicitly been predicated on descriptive theories of reference. To rectify this, we attempt to demonstrate how a causal theory can be applied to intentional concepts. Specifically, we argue that some phenomena in early social development (e.g., mimicry, gaze following, and emotional contagion) can serve as reference fixers that enable children to track others’ intentional states and, thus, to refer to those states. This allows intentional concepts to be anchored to their referents, even if folk psychological descriptions turn out to be false.

In a previous paper (Simon and Groen 1973) it was proposed that theories of empirical phenomena should satisfy conditions of finite and irrevocable testability (FITness conditions). Roughly speaking, a theory is finitely testable if, for every set of observations that falsifies the theory, there exists a finite subset of observations that falsifies it. A theory is irrevocably testable if, for any finite set of observations that falsifies the theory, any superset of observations that includes that set also falsifies it—a theory falsified by observations cannot be resuscitated by adding new observations to the original set.

Current computational psychology, especially as described by Fodor (1975, 1980, 1981), Pylyshyn (1980), and Stich (1983), is both a bold, promising program for cognitive science and an alternative to naturalistic psychology (Putnam 1975). Whereas naturalistic psychology depends on the general scientific framework to fix the meanings of general terms and, hence, the content of thoughts utilizing or expressed in those terms, computational cognitive theory banishes semantical considerations in psychological investigations, embracing methodological, not ontological, solipsism. I intend to argue that computational psychology cannot individuate thoughts as it promises. For, semantics is fundamental in fixing an important subset of the computational relations that, according to the computational theory, are supposed both to obtain among thoughts and, thereby, to determine their identity conditions. If what I contend is correct, then contrary to what its advocates maintain, computational psychology is not preferable to naturalistic psychology as a research strategy in cognitive science.

The relation between models and the world is mediated by experimental procedures generating data that are used as evidence to evaluate the model. Data can serve as empirical evidence, for or against, only if they result from reliable experimental procedures. The aim of this article is to discuss the role of relevance judgments in the evaluation of reliability and to clarify the conditions under which reliability can be a strictly empirical matter. It is argued that reliability is a strictly empirical issue only in the restricted case in which the claim under test/investigation is about a data-generating procedure.

Cases in which people are self-deceived seem to require that the person hold two contradictory beliefs, something which appears to be impossible or implausible. A phenomenon seen in some brain-damaged patients known as confabulation (roughly, an ongoing tendency to make false utterances without intent to deceive) can shed light on the problem of self-deception. The conflict is not actually between two beliefs, but between two representations, a ‘conceptual’ one and an ‘analog’ one. In addition, confabulation yields valuable clues about the structure of normal human knowledge-gathering processes.

Theory and Practice; Precision and Vagueness. There has long been a conflict between the theory and the practice of scientific naming. The theory expressed both by working scientists and by philosophers has almost always been that precision is an essential part of the scientific attitude and of the procedures and results of science. Theoretically, metaphors have been scorned as belonging to poetry or to philosophy rather than to science. In scientific practice, however, vagueness and metaphor are constantly present; and they are particularly evident at the advancing frontiers of any science, whether mathematical, natural, or social.