Relying on the universality of quantum mechanics and on recent results known as the “threshold theorems,” quantum information scientists deem the question of the feasibility of large-scale, fault-tolerant, and computationally superior quantum computers as purely technological. Reconstructing this question in statistical mechanical terms, this article suggests otherwise by questioning the physical significance of the threshold theorems. The skepticism it advances is neither too strong (hence is consistent with the universality of quantum mechanics) nor too weak (hence is independent of technological contingencies).

Goodman's paradox gives rise to a cluster of problems, problems that are in need of different answers. I will discuss some variants of the grue hypothesis applied to the technological context. One conclusion in this paper is that there is room for rational decisions, and that solutions to the paradoxes in technology can be found in the practical choice situation.

Helen Longino's “contextual empiricism” is one of the most sophisticated recent attempts to defend a social theory of science. On this view, objectivity and epistemic acceptability require that research be produced within communities that approximate a Millian marketplace of ideas. I argue, however, that Longino's embedding of her epistemology within the framework of Mill's political liberalism implies a conception of individual epistemic agents that is incompatible with her view that scientific knowledge is necessarily social, and I begin to articulate an alternative conception that is better suited to a truly social theory of science.

We have argued elsewhere that natural selection is not a cause of evolution, and that a resolution-of-forces (or vector addition) model does not provide us with a proper understanding of how natural selection combines with other evolutionary influences. These propositions have come in for criticism recently, and here we clarify and defend them. We do so within the broad framework of our own ‘hierarchical realization model’ of how evolutionary influences combine.

Quantum field theory (QFT) presents a genuine example of the underdetermination of theory by empirical evidence. There are variants of QFT—for example, the standard textbook formulation and the rigorous axiomatic formulation—that are empirically indistinguishable yet support different interpretations. This case is of particular interest to philosophers of physics because, before the philosophical work of interpreting QFT can proceed, the question of which variant should be subject to interpretation must be settled. New arguments are offered for basing the interpretation of QFT on a rigorous axiomatic variant of the theory. The pivotal considerations are the roles that consistency and idealization play in this case.

This article explores Michael Faraday's “Historical Sketch of Electro-Magnetism” as a fruitful source for understanding the epistemic significance of experimentation. In this work Faraday provides a catalog of the numerous experimental and theoretical developments in the early history of electromagnetism. He also describes methods that enable experimentalists to dissociate experimental results from the theoretical commitments generating their research. An analysis of the methods articulated in this sketch is instructive for confronting epistemological worries about the theory-dependence of experimentation.

Because contemporary scientific research is conducted by groups of scientists, understanding scientific progress requires understanding this division of cognitive labor. We present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to find the most epistemically significant research approaches. We consider three different search strategies that scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community influence their actions. This is compared with two social research strategies: Followers are biased toward what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform the other strategies. Finally, we show that, in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains.

What, if anything, is wrong with typological thinking? The question is important, for some evolutionary developmental biologists appear to espouse a form of typology. I isolate four allegations that have been brought against it. They include the claim that typological thinking is mystical; the claim that typological thinking is at odds with the fact of evolution; the claim that typological thinking is committed to an objectionable metaphysical view, which Elliott Sober calls the ‘natural state model’; and finally the view (endorsed by Ron Amundson and Günter Wagner) that typological thinking—and specifically evolutionary developmental biology's typological thinking—is committed to a peculiar form of causation that does not fit neatly into the causal models endorsed by population genetics. I argue that, properly understood, the typological thinking of evolutionary developmental biology does not run into any of these problems.

This paper evaluates a general argument for the conclusion that visual representations in science must play the role of truth bearers if they are to figure as legitimate contributors to scientific arguments and explanations. The argument is found to be unsound. An alternative approach to assessing the role of visual representations in science is exemplified by an examination of the role of structural formulas in organic chemistry. Structural formulas are found not to play the role of truth bearers; nonetheless, they contribute to the arguments and explanations of organic chemistry. An early success of conformational analysis is presented in order to illustrate the role of structural formulas in the discourse of organic chemistry.

The claim that a functional kind is multiply realized is typically motivated by appeal to intuitive examples. We are seldom told explicitly what the relevant structures are, and people have often preferred to rely on general intuitions in these cases. This article deals with the problem by explaining how to understand the proper relation between structural kinds and the functions they realize. I will suggest that the structural kinds that realize a function can be properly identified by attending to the context of functional explanation.

To what extent does the design of statistical experiments, in particular sequential trials, affect their interpretation? Should postexperimental decisions depend on the observed data alone, or should they account for the used stopping rule? Bayesians and frequentists are apparently deadlocked in their controversy over these questions. To resolve the deadlock, I suggest a three-part strategy that combines conceptual, methodological, and decision-theoretic arguments. This approach maintains the pre-experimental relevance of experimental design and stopping rules but vindicates their evidential, postexperimental irrelevance.

This article addresses Paul Churchland's attempt to identify colors with surface reflectance spectra. Of particular concern is Churchland's novel method of approximating surface reflectance spectra. While those approximations are generated by objective means and yield a striking match with human phenomenological color space, they are not physically meaningful. The reason for this is that the method used to produce the approximations induces equivalence classes on surface reflectances that are not invariant under physically appropriate changes of measurement convention. This result undermines Churchland's proposed response to the objection from metamers commonly raised against color physicalism, as his surface reflectance approximations are supposed to provide an objective, physical unifying basis for metamers.

Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter's regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable in ideal evidential circumstances (i.e., when evidence is concordant), often when a variety of evidence is available from multiple techniques, the evidence is discordant.

The two books discussed here make important contributions to our understanding of the role of spacetime concepts in physical theories and how that understanding has changed during the evolution of physics. Both emphasize what can be called a ‘dynamical’ account, according to which geometric structures should be understood in terms of their roles in the laws governing matter and force. I explore how the books contribute to such a project; while generally sympathetic, I offer criticisms of some historical claims concerning Newton, and argue that the dynamical account does not undercut ontological issues as the books claim.

The present text comments on Steel 2005, in which the author claims to extend from the deterministic to the general case, the result according to which the causal Markov condition is satisfied by systems with jointly independent exogenous variables. I show that Steel's claim cannot be accepted unless one is prepared to abandon standard causal modeling terminology. Correlatively, I argue that the most fruitful aspect of Steel 2005 consists in a realist conception of error terms, and I show how this conception sheds new light on the relationship between determinism and the causal Markov condition.