Philosophical discussions of information and specificity in biology are now commonplace, but no consensus exists about whether the privileging of genetic causation in investigation and explanation is justified. However, little effort has been expended on understanding practices when scientists experimentally measure information or causal specificity. An example of this type of practice—measuring positional information in gene expression during pattern formation in embryogenesis—shows that biologists are unconcerned with comparing the amount of information in genes with that of other factors. Instead, they focus on whether the measured causal specificity explains the phenomenon under scrutiny.

When solving a complex problem in a group, should group members always choose the best available solution that they are aware of? In this paper, I build simulation models to show that, perhaps surprisingly, a group of agents who individually randomly follow a better available solution than their own can end up outperforming a group of agents who individually always follow the best available solution. This result has implications for the feminist philosophy of science and social epistemology.

Economists often consult multiple models in order to combat model uncertainty in the face of misspecification. By examining modeling practices at the Bank of England, this paper identifies an important, but underappreciated modeling procedure. Sometimes an idealized model is manipulated to reproduce the results from another distinct auxiliary model, ones which it could not produce on its own. However, this procedure does not involve making the original model “more realistic,” insofar as this means adding in additional causal factors. This suggests that there are ways to make models more representationally adequate that do not involve de-idealization in the straightforward sense.

It has been suggested that particle physics has reached the “dawn of the post-naturalness era.” I explain the current shift in particle physicists’ attitude toward naturalness. I argue that the naturalness principle was perceived to be supported by theories it has inspired. The potential coherence between major beyond the standard model (BSM) proposals and the naturalness principle led to an increasing degree of credibility of the principle among particle physicists. The absence of new physics at the Large Hadron Collider (LHC) has undermined the potential coherence and has led to the principle’s loss of significance.

According to Skow, correct answers to why questions cite only causes or grounds, but not nonaccidental regularities. Accounts that cite nonaccidental regularities typically confuse second-level reasons with first-level reasons. Only causes and grounds are first-level reasons why. Nonaccidental regularities are second-level reasons why. I first show that Skow’s arguments for the accusation of confusion depend on the independent thesis that only citations of first-level reasons why are (parts of) answers to why questions. Then I argue that this thesis is false. Consequently, the claim that correct answers to why questions cite only causes or grounds is refuted as well.

Among advocates and critics of the “extended evolutionary synthesis” (EES), “reciprocal causation” refers to the view that adaptive evolution is a bidirectional phenomenon, whereby organisms and environments impinge on each other through processes of niche construction and natural selection. I argue that reciprocal causation is incompatible with the view that natural selection is a metaphysically emergent causal process. The emergent character of selection places reciprocal causation on the horns of dilemma, and neither horn can rescue it. I conclude that proponents of the EES must abandon the claim that the process of natural selection features in cycles of reciprocal causation.

Confirmation is a graded notion: evidence can confirm a hypothesis to a greater or lesser degree. There has been debate about how to measure degree of confirmation. Starting from the observation that we would like evidence to be a discriminating indicator of truth, we conduct computer simulations to determine how well the various known measures of confirmation predict the extent to which a given piece of evidence fulfills that role, given a hypothesis of interest. The outcomes show that some measures are markedly better indicators of truth than others.

The problem of theory choice and model selection is hard but still important when useful truths are underdetermined, perhaps not by all kinds of data but by the kinds of data we can have access to ethically or practicably—even if we have an infinity of such data. This article addresses a crucial instance of that problem: the problem of inferring causal structures from nonexperimental, nontemporal data without assuming the so-called causal Faithfulness condition or the like. A new account of epistemic evaluation is developed to solve that problem and justify a standard practice of causal inference in data science.

Most accounts of mechanism discovery have focused on mechanisms that perform the work required to produce a phenomenon. These mechanisms are often subject to regulation by control mechanisms. Using the example of the molecular motor dynein, this paper examines one process by which such control mechanisms are discovered—the process by which researchers, after identifying additional components required to produce the phenomenon but not directly involved in the work of producing that phenomenon, investigate both how these components act on the original mechanism and how they do so in response to measurements of conditions relevant to the operation of the controlled mechanism.

D. Miller's demonstrations of the language dependence of truthlikeness raise a profound problem for the claim that scientific progress is objective. In two recent papers (Barnes 1990, 1991) I argue that the objectivity of progress may be grounded on the claim that the aim of science is not merely truth but knowledge; progress thus construed is objective in an epistemic sense. In this paper I construct a new solution to Miller's problem grounded on the notion of “approximate causal explanation” which allows for linguistically invariant progress outside an epistemic context. I suggest that the notion of “approximate causal explanation” provides the resources for a more robust theory of progress than that provided by the notion of “approximate truth.”

In part one of this paper we shall elucidate an operational concept of logical simplicity as it seems to function in natural science. Although this is a tentative and exploratory formulation, its novelty, relative to the great European philosophical tradition, seems to require a preliminary warning about misunderstandings.

In Part Two we shall apply the formulation to social inquiry and make a positive suggestion for further development of the proposal.

I show that van Fraassen's empiricism leads to mutually incompatible claims with regard to empirical theories. He is committed to the claim that reasons for accepting a theory and believing it are always identical, insofar as the theory in question is an empirical theory. He also makes a general claim that reasons for accepting a theory are not always reasons for believing it irrespective of whether the theory is an empirical theory.

Prior to statistical mechanics and especially before the advent of the new quantum mechanics, it was traditionally held, following in the main the Kantian philosophy, that the task of science is to attain a unique quantitative representation of reality. It was thought—and with justifiable zeal—that a scientific discipline is exact to the extent to which a mathematical pattern yielding quantitative relations can be applied to its subject matter. This view was based on the implicit assumptions that functional relatedness conducive to quantitative evaluation is bound to reveal the most generic, and hence, the most essential traits of events.

What I propose to do in the present paper is to clarify critical realism on some crucial points. While such is my primary purpose, I also entertain the hope that logical positivists and pragmatists may be led to see in this form of realism a necessary supplementation to their emphases and insights. I am persuaded that there has been misunderstanding and prejudice at work partly because of verbal phobias in connection with such phrases as the copy-theory, representative perception, transcendence, the subjective, Cartesian dualism, etc., etc. So strong have these accumulated prejudices been that, in America at least, there has been a tendency to outlaw epistemology. I do not find the same situation in England for instance. Here it seems at times as though pragmatism and positivism have consciously “ganged up” against epistemology—in my opinion to the hurt of philosophy. I have the impression that the younger philosophers in America are bewildered and are largely drifting. Under these conditions it is the duty of any one who believes that he has a clear-cut epistemology capable of rising above these verbal phobias to seek to present it as precisely as possible.

In her “Species Are Individuals” (1985), Mary Williams offers informal arguments and a sketched proof which allegedly show that species are individuals with respect to evolutionary theory. In this paper, I suggest that her informal arguments are insufficient for showing that clans are not sets and that species are individuals. I also argue that her sketched proof depends on three questionable assumptions.

A common objection to adaptationist accounts of human emotions is that they ignore the influence of culture. If complex emotions like guilt, shame and romantic jealousy are largely culturally determined, how could they be biological adaptations? Dual inheritance models of gene/culture coevolution provide a potential answer to this question. If complex emotions are developmentally ‘scaffolded’ by norms that are transmitted from parent to offspring with reasonably high fidelity, then these emotions can evolve to promote individual reproductive interests. This paper draws on case studies of emotional development to illustrate how complex emotions satisfy these conditions. Many of the norms and parenting strategies influencing emotional development are absorbed during the early stages of life when a child is in primary contact with its parents and before the onset of complex cognition. These conditions make it likely that emotion-governing norms are transmitted vertically and with relatively little cognitive ‘contamination’.

Scientists are people. They are not “people, but…”. They have not escaped and cannot escape the “democentric” predicament. They are members of a society, no matter how hard they strain to be individualistic or exclusively clannish. If they succeed in being members of a small clan or a club they can be credited possibly with having more or less shrunk only the apparent size of their society, without escaping in any significant manner the social field implied in being “people”. If they attempt a greater shrinkage than that, they court complete frustration. To verify that, try, if you will, to imagine a thoroughly solitary scientist on a desert isle. Is he not alone and at last an illustration of the ungrammatical and even logically fictitious singular of the word “people”? No, he is definitely and hopelessly not alone, unless he first forgets even as habit everything he has learned from people. And, if he does that, he is no longer a scientist or even the rudiments of one. Indeed he must be reduced at least to the status of an animal, and an extremely unsocial one at that, because by the terms of our imaginary experiment, he must not join any other society, even if it were of but “animal-people”, e.g. a wolf-pack or an ant-hill culture, where he might learn something from others. Such strictness in argument is introduced only to drive home the fact that what constitutes “people” is derived from the dimmest animal past, where language is still unspoken and is constituted of simple actions taken together, literally concepts. The “con” in “concept” tends to be forgotten. We underscore it.

The recent work of Paul Teller and Sunny Auyang in the philosophy of Quantum Field Theory (QFT) has stimulated the search for the fundamental entities in this theory. In QFT, the classical notion of a particle collapses. The theory does not only exclude classical, i.e., spatiotemporally identifiable particles, but it makes particles of the same type conceptually indistinguishable. Teller and Auyang have proposed competing ersatz-ontologies to account for the ‘loss of particles’: field quanta vs. field events. Both ontologies, however, suffer from serious defects. While quanta lack numerical identity, spatiotemporal localizability, and independence of basis-representations, events—if understood as concrete measurement events—are related to the theory only statistically. I propose an alternative solution: The entities of QFT are events of the type ‘Quantum system, S, is in quantum state, Ψ‘. These are not point events, but Davidsonian events, i.e., they can be identified by their location within the causal net of the world.