P.D. Magnus

Thomas Reid is often misread as defending common sense, if at all, only by relying on illicit premises about God or our natural faculties. On these theological or reliabilist misreadings, Reid makes common sense assertions where he cannot give arguments. This paper attempts to untangle Reid's defense of common sense by distinguishing four arguments: (a) the argument from madness, (b) the argument from natural faculties, (c) the argument from impotence, and (d) the argument from practical commitment. Of these, (a) and (c) do rely on problematic premises that are no more secure than claims of common sense itself. Yet (b) and (d) do not. This conclusion can be established directly by considering the arguments informally, but one might still worry that there is an implicit premise in them. In order to address this concern, I reconstruct the arguments in the framework of subjective Bayesianism. The worry becomes this: Do the arguments rely on specific values for the prior probability of some premises? Reid's appeals to our prior cognitive and practical commitments do not. Rather than relying on specific probability assignments, they draw on things that are part of the Bayesian framework itself, such as the nature of observation and the connection between belief and action. Contra the theological or reliabilist readings, the defense of common sense does not require indefensible premises.

The Homeostatic Property Cluster (HPC) account of natural kinds has become popular since it was proposed by Richard Boyd in the late 1980s. Although it is often taken as a defining natural kinds as such, it is easy enough to see that something's being a natural kind is neither necessary nor sufficient for its being an HPC. This paper argues that it is better not to understand HPCs as defining what it is to be a natural kind but instead as providing the ontological realization of (some) natural kinds.

An introduction to sentential logic and first-order predicate logic with identity, logical systems that significantly influenced twentieth-century analytic philosophy. After working through the material in this book, a student should be able to understand most quantified expressions that arise in their philosophical reading. This books treats symbolization, formal semantics, and proof theory for each language. The discussion of formal semantics is more direct than in many introductory texts. Although forall x does not contain proofs of soundness and completeness, it lays the groundwork for understanding why these are things that need to be proven. The book highlights the choices involved in developing sentential and predicate logic. Students should realize that these two are not the only possible formal languages. In translating to a formal language, we simplify and profit in clarity. The simplification comes at a cost, and different formal languages are suited to translating different parts of natural language.

This paper gives a characterization of distributed cognition (d-cog) and explores ways that the framework might be applied in studies of science. I argue that a system can only be given a d-cog description if it is thought of as performing a task. Turning our attention to science, we can try to give a global d-cog account of science or local d-cog accounts of particular scientific projects. Several accounts of science can be seen as global d-cog accounts: Robert Merton's sociology of scientific norms, Philip Kitcher's 20th-century account of cognitive labor, and Kitcher's 21st-century notion of well-ordered science. Problems that arise for them arise just because of the way that they attribute a function to science. The paper concludes by considering local d-cog accounts. Here, too, the task is the crux of the matter.

It seems obvious that a community of one thousand scientists working together to make discoveries and solve puzzles should arrange itself differently than would one thousand scientist-hermits working independently. Because of limited time, resources, and attention, an independent scientist can explore only some of the possible approaches to a problem. Working alone, each hermit would explore the most promising approaches. They would needlessly duplicate the work of others and would be unlikely to develop approaches which look unpromising but really have tremendous potential. Contrariwise, a large community can more rigorously explore the space of possible approaches. Most scientists should work on the most promising approaches, but a smaller number can be committed to approaches that initially look less promising. Exploratory work can reveal if one of those initially unpromising approaches has unrealized potential, and more scientists can adopt it once its potential becomes more apparent

Philosophy of science in the past half century can be seen as a reaction against logical empiricism's focus on modern logic as the format in which debates should be expressed and on physics as the canonical science. These reactions have resulted in a fragmentation of the field. Although this provides ways forward for disparate philosophies of various sciences, it threatens the very possibility of general philosophy of science. The debate that most obviously continues to be conducted at the general level—the debate about scientific realism—only does so because of a dangerous naïveté. Nevertheless, this article suggests that there is a place for general work not by starting at the highest level of abstraction but instead by abstracting general lessons from actual science

The accepted narrative treats John Stuart Mill’s Kinds as the historical prototype for our natural kinds, but Mill actually employs two separate notions: Kinds and natural groups. Considering these, along with the accounts of Mill’s nineteenth-century interlocutors, forces us to recognize two distinct questions. First, what marks a natural kind as worthy of inclusion in taxonomy? Second, what exists in the world that makes a category meet that criterion? Mill’s two notions offer separate answers to the two questions: natural groups for taxonomy and Kinds for ontology. This distinction is ignored in many contemporary debates about natural kinds and is obscured by the standard narrative that treats our natural kinds just as a development of Mill’s Kinds.

Within philosophy of science, debates about realism often turn on whether posited entities exist or whether scientific claims are true. Natural kinds tend to be investigated by philosophers of language or metaphysicians, for whom semantic or ontological considerations can overshadow scientific ones. Since science crucially involves dividing the world up into categories of things, however, issues concerning classification ought to be central for philosophy of science. Muhammad Ali Khalidi's book fills that gap, and I commend it to readers with an interest in scientific taxonomy and natural kinds. He works through general issues to craft a useful philosophical conception and uses the account to think through a wide range of specific examples. Although there are differences in the details, that one-sentence summary of Khalidi's book could just as well describe my own recent monograph on natural kinds.

If two theory formulations are merely different expressions of the same theory, then any problem of choosing between them cannot be due to the underdetermination of theories by data. So one might suspect that we need to be able to tell distinct theories from mere alternate formulations before we can say anything substantive about underdetermination, that we need to solve the problem of identical rivals before addressing the problem of underdetermination. Here I consider two possible solutions: Quine proposes that we call two theories identical if they are equivalent under a reconstrual of predicates, but this would mishandle important cases. Another proposal is to defer to the particular judgements of actual scientists. Consideration of an historical episodethe alleged equivalence of wave and matrix mechanicsshows that this second proposal also fails. Nevertheless, I suggest, the original suspicion is wrong; there are ways to enquire into underdetermination without having solved the problem of identical rivals.

There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential contexts, we can see that neither weak nor strong predictivism captures all of the reasons for valuing prediction available. A third path is presented, Pluralist Instrumental Predictivism; PIP for short.

On-line, just as off-line, there are ways of assessing the credibility of information sources. The Internet, although it arguably makes for nothing wholly new in this regard, complicates the ordinary task of assessing credibility. In the first section, I consider a specific example and argue that Internet content providers have no clear interest in resolving these comlications. In the second, I consider four general ways that we might assess credibility and explore how they apply to life online. Finally, I argue that even careful information gathering may pose subtle pitfalls but that some of these may be mitigated on-line.

According to the standard narrative, natural kind is a technical notion that was introduced by John Stuart Mill in the 1840s and the recent craze for natural kinds, launched by Putnam and Kripke, is a continuation of that tradition. I argue that the standard narrative is mistaken. The Millian tradition of kinds was not particularly influential in the 20th-century, and the Putnam-Kripke revolution did not clearly engage with even the remnants that were left of it. The presently active tradition of natural kinds is less than half a century old. Recognizing this might help us better appreciate both Mill and natural kinds.

Debates about the underdetermination of theory by data often turn on specific examples. Cases invoked often enough become familiar, even well worn. Since Helen Longino’s discussion of the case, the connection between prenatal hormone levels and gender-linked childhood behaviour has become one of these stock examples. However, as I argue here, the case is not genuinely underdetermined. We can easily imagine a possible experiment to decide the question. The fact that we would not perform this experiment is a moral, rather than epistemic, point. Finally, I suggest that the ”underdetermination’ of the case may be inessential for Longino to establish her central claim about it.

The accepted narrative treats John Stuart Mill's Kinds as the historical prototype for our natural kinds, but Mill actually employs two separate notions: Kinds and natural groups. Considering these, along with the accounts of Mill's 19th-century interlocutors, forces us to recognize two distinct questions. First, what marks a natural kind as worthy of inclusion in taxonomy? Second, what exists in the world that makes a category meet that criterion? Mill's two notions offer separate answers to the two questions: natural groups for taxonomy, and Kinds for ontology. This distinction is ignored in many contemporary debates about natural kinds and is obscured by the standard narrative which treats our natural kinds just as a development of Mill's Kinds.

The underdetermination of theory by evidence is supposed to be a reason to rethink science. It is not. Many authors claim that underdetermination has momentous consequences for the status of scientific claims, but such claims are hidden in an umbra of obscurity and a penumbra of equivocation. So many various phenomena pass for `underdetermination' that it's tempting to think that it is no unified phenomenon at all, so I begin by providing a framework within which all these worries can be seen as species of one genus: A claim of underdetermination involves (at least implicitly) a set of rival theories, a standard of responsible judgment, and a scope of circumstances in which responsible choice between the rivals is impossible. Within this framework, I show that one variety of underdetermination motivated modern scepticism and thus is a familiar problem at the heart of epistemology. I survey arguments that infer from underdetermination to some reëvaluation of science: top-down arguments infer a priori from the ubiquity of underdetermination to some conclusion about science; bottom-up arguments infer from specific instances of underdetermination, to the claim that underdetermination is widespread, and then to some conclusion about science. The top-down arguments either fail to deliver underdetermination of any great significance or (as with modern scepticism) deliver some well-worn epistemic concern. The bottom-up arguments must rely on cases. I consider several promising cases and find them to either be so specialized that they cannot underwrite conclusions about science in general or not be underdetermined at all. Neither top-down nor bottom-up arguments can motivate any deep reconsideration of science.