The failure of the attempt by Michael Polanyi to capture the social organization of science by comparing it to the operation of a market bears salutary lessons for modern philosophers of science in their rush to appropriate market models and metaphors. In this case, an initially plausible invisible hand argument ended up as crude propaganda for the uniquely privileged social support of science.

Most attempts to define culture as used in the cultural evolution literature treat culture as a single phenomenon that can be given a single nondisjunctive definition. In this article I argue that, really, cultural evolutionists employ a variety of distinct but closely related concepts of culture. I show how the main prominent attempts to define a culture concept fail to properly capture all the uses of “culture” employed in cultural evolutionary work. I offer a description of some of the most important culture concepts used by cultural evolutionists.

This article explores some ways in which philosophical theories of causation and empirical investigations into causal learning and judgment can mutually inform one another.

I analyze the extent to which classical phase transitions, both first order and continuous, pose a challenge for intertheoretic reduction. My contention is that phase transitions are compatible with a notion of reduction that combines Nagelian reduction and what Thomas Nickles called Reduction2. I also argue that, even if the same approach to reduction applies to both types of phase transitions, there is a crucial difference in their physical treatment: in addition to the thermodynamic limit, in continuous phase transitions there is a second infinite limit involved, which marks an important difference in the reduction of first-order and continuous phase transitions.

The place of induction in the framing and test of scientific hypotheses is investigated. The meaning of ‘induction’ is first equated with generalization on the basis of case examination. Two kinds of induction are then distinguished: the inference of generals from particulars (first degree induction), and the generalization of generalizations (second degree induction). Induction is claimed to play a role in the framing of modest empirical generalizations and in the extension of every sort of generalizations—not however in the invention of high-level hypotheses containing theoretical predicates. It is maintained, on the other hand, that induction by enumeration is essential in the empirical test of the lowest-level consequences of scientific theories, since it occurs in the drawing of “conclusions” from the examination of empirical evidence. But it is also held that the empirical test is insufficient, and must be supplemented with theorification, or the expansion of isolated hypotheses into theories. Refutation is not viewed as a substitute for confirmation but as its complement, since the very notion of unfavorable case is meaningful only in connection with the concept of positive instance. Although the existence of an inductive method is disclaimed, it is maintained that the various patterns of plausible reasoning (inductive inference included) are worth being investigated. It is concluded that scientific research follows neither the advice of inductivism nor the injunction of deductivism, but takes a middle course in which induction is instrumental both heuristically and methodologically, although the over-all pattern of research is hypothetico-deductive.

1. Introduction. It is generally admitted that a large part of man's knowledge is based on inductive arguments. Hence any philosophical theory concerning the nature of inductive arguments constitutes an epistemological theory. Any such philosophical theory of induction must, if it is to be satisfactory, take adequate account of Hume's criticism of inductive arguments. One way of treating his criticism is to say that the validity of inductive arguments is in an important sense relative to some broad factual assumptions about the general nature of the universe and that these general factual assumptions are presupposed in a certain way by the users of inductive arguments (8, 10). Let us call any theory of this general type a postulate theory of induction.

This article shows that a slight variation of the argument in Milne 1996 yields the log-likelihood ratio l rather than the log-ratio measure r as “the one true measure of confirmation.”

I argue that collaborators do not need to reach broad agreement over the justification of a consensus claim. This is because maintaining a diversity of justifiers within a scientific collaboration has important epistemic value. I develop a view of collective justification that depends on the diversity of epistemic perspectives present in a group. I argue that a group can be collectively justified in asserting that P as long as the disagreement among collaborators over the reasons for P is itself justified. In conclusion, I make a case for multimethod collaborative research and work through an example in the social sciences.

Debates on the contingency of history have largely focused on the history of life. This article targets the supposed contingency of human history. It does not defend a global claim about the overall contingency of history. Rather, it aims to identify and explain the difference between robust and fragile historical trajectories. It does so by considering a set of contrasting cases and identifying critical differences among the cases. The analysis shows that one important source of contingency is the historical emergence of command-and-control institutions; one important source of robustness is the existence of population-level processes structured by relatively stable institutions.

Evolutionary convergence is often appealed to in support of claims about multiple realization. The idea is that convergence shows that the same function can be realized by different kinds of structures. I argue here that the nature of convergence is more complicated than it might appear at first look. Broad claims about convergence are made by biologists during general discussions of the mechanisms of evolution. In their specialized work, though, biologists are often more limited in the claims they make. I will examine a standard example to show how claims about convergence can be oversimplified.

Until recently, economics was generally understood to be a nonexperimental science with a hypothetico-deductive methodology. This article considers how the methodology of economics has changed with the spread of experimental methods. Initially, most experimental economists saw their work as testing pre-existing theories. However, a method of systematic inductive enquiry in which theory plays a less central role is now evolving. This method is structured around the discovery and progressive refinement of regularities. “Exhibits”—experimental designs that generate significant regularities—are taking over some of the functions formerly performed by theoretical models.

Prominent defenders of the extended cognition thesis have looked to evolutionary theory for support. Roughly, the idea is that natural selection leads one to expect that cognitive strategies should exploit the environment, and exploitation of the right sort results in a cognitive system that extends beyond the head of the organism. I argue that proper appreciation of evolutionary theory should create no such expectation. This leaves open whether cognitive systems might in fact bear a relationship to the environment that leads to their extension.

Mechanisms are usually viewed as hierarchical, with lower levels of a mechanism influencing, and decomposing, its higher-level behavior. To draw quantitative predictions from a model of a mechanism, the model must capture this hierarchical aspect. Recursive Bayesian networks (RBNs) were put forward by Lorenzo Casini et al. as a means to model mechanistic hierarchies by decomposing variables into their constituting causal networks. The proposal was criticized by Alexander Gebharter. He proposes an alternative formalism, which instead decomposes arrows. Here, I defend RBNs from the criticism and argue that they offer a better representation of mechanistic hierarchies than the rival account.

This paper counters an objection raised against one of Bertrand Russell's lesser-known epistemological views, viz. “structural realism” (SR). In short, SR holds that at most we have knowledge of the structure of the external (i.e., physical) world. M. H. A. Newman's allegedly fatal objection is that SR is either trivial or false. I argue that the accusation of triviality is itself empty since it fails to establish that SR knowledge claims are uninformative. Moreover, appealing to Quine's notion of ontological relativity, I suggest that far from being false, SR knowledge claims seem to be the most that we can hope for.

This article investigates the relationship between two evaluative claims about agents’ degrees of belief: (i) that it is better to have more rather than less accurate degrees of belief and (ii) that it is better to have less rather than more probabilistically incoherent degrees of belief. We show that, for suitable combinations of inaccuracy measures and incoherence measures, both claims are compatible, although not equivalent; moreover, certain ways of becoming less incoherent always guarantee improvements in accuracy. Incompatibilities between particular incoherence and inaccuracy measures can be exploited to argue against particular ways of measuring either inaccuracy or incoherence.

Recently, there has been a rise in pessimism concerning what theoretical ecology can offer conservation biologists in the formation of reasonable environmental policies. In this paper, I look at one of the pessimistic arguments offered by Kristin Shrader-Frechette and E. D. McCoy (1993, 1994)—the argument from conceptual imprecision. I suggest that their argument rests on an inadequate account of the concepts of ecological stability and that there has been conceptual progress with respect to complexity-stability hypotheses. Such progress, I maintain, can supply important resources for conservation biologists in determining environmental policies.

In a reply to Nicholas Maxwell, Stein has proved that Minkowski spacetime can leave room for the kind of indeterminateness required both by certain interpretations of quantum mechanics and by objective becoming. By examining the consequences of outcome dependence in Bell-type experiments for the co-determinateness of spacelike-related events, I argue that the only becoming relation that is compatible with both causal and noncausal readings of the quantum correlations is the universal relation. This result might also undermine interpretations of quantum mechanics requiring non-epistemically indeterminate states before measurement and hyperplane-dependent wave collapse.

We show that as a chain of confirmation becomes longer, confirmation dwindles under screening-off. For example, if E confirms H1, H1 confirms H2, and H1 screens off E from H2, then the degree to which E confirms H2 is less than the degree to which E confirms H1. Although there are many measures of confirmation, our result holds on any measure that satisfies the Weak Law of Likelihood. We apply our result to testimony cases, relate it to the Data-Processing Inequality in information theory, and extend it in two respects so that it covers a broader range of cases.

The aim of this paper is to introduce the instrumental variables technique to the discussion about causal inference in econometrics. I show that it may lead to causally incorrect conclusions unless some fairly strong causal background assumptions are made, assumptions which are usually left implicit by econometricians. These assumptions are very similar to, albeit not identical with, James Woodward's definition of an ‘intervention’. I discuss similarities and differences of the two points of view and argue that—understood as a practical method of causal inference—the set presented here is superior.