The British Journal for the Philosophy of Science最新文献

Probably the most dramatic historical challenge to scientific realism concerns Arnold Sommerfeld's ([1916]) derivation of the fine structure energy levels of hydrogen. Not only were his predictions good, he derived exactly the same formula that would later drop out of Dirac's 1928 treatment (something not possible using 1925 Schrödinger-Heisenberg quantum mechanics). And yet the most central elements of Sommerfeld's theory were not even approximately true: his derivation leans heavily on a classical approach to elliptical orbits, including the necessary adjustments to these orbits demanded by relativity. Even physicists call Sommerfeld's success a 'miracle', which rather makes a joke of the so-called 'no miracles argument'. However, this can all be turned around. Here I argue that the realist has a story to tell vis-à-vis the discontinuities between the old and the new theory, leading to a realist defence based on sufficient continuity of relevant structure. 1Introduction2No Realist Commitment Required?3Enter the Physicists4A New Approach to the Non-relativistic Success5Relativity and Spin6Structure and Realist Commitment7Conclusion.

Biochemical kinds such as proteins pose interesting problems for philosophers of science, as they can be studied from the points of view of both biology and chemistry. The relationship between the biological functions of biochemical kinds and the microstructures that they are related to is the key question. This leads us to a more general discussion about ontological reductionism, microstructuralism, and multiple realization at the biology-chemistry interface. On the face of it, biochemical kinds seem to pose a challenge for ontological reductionism and hence motivate a dual theory of chemical and biological kinds, a type of pluralism about natural kinds. But it will be argued that the challenge, which is based on multiple realization, can be addressed. The upshot is that there are reasonable prospects for ontological reductionism about biochemical kinds, which corroborates natural kind monism. 1Introduction2Functions: Aetiological or Goal-Directed?3Moonlighting and Multiple Determinations4The Powers-Based Subset Strategy5The Case of Haemoglobin6Haemoglobin and the Problem of Lower-Level Vengeance7Multiple Realization and (Higher-Order) Interest Relativeness8The Prospects for Ontological Reductionism.

In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model-world relation, which is the relation in virtue of which successful models are successful. Weisberg's main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg's account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models' epistemic success. I consider three potential ways of concretizing the concept of shared features: as identical, quantitatively sufficiently close, and sufficiently similar features. I argue that each of these concretizations faces significant challenges, leaving unclear how Weisberg's account substantially contributes to elucidating the relation in virtue of which successful models are successful. Against this background, I outline a pluralistic revision and argue that this revision may not only help Weisberg's account evade several of the problems that I raise, but also offers a novel perspective on the model-world relation more generally. 1Introduction2Weisberg's Feature-Sharing Account3What Is a Shared Feature? 3.1Identity3.2Sufficient closeness3.3Sufficient similarity4Turning Weisberg's Account 'Upside Down'5Conclusion.

While the fundamental laws of physics are time-reversal invariant, most macroscopic processes are irreversible. Given that the fundamental laws are taken to underpin all other processes, how can the fundamental time-symmetry be reconciled with the asymmetry manifest elsewhere? In statistical mechanics (SM), progress can be made with this question. What I dub the 'Zwanzig-Zeh-Wallace framework' can be used to construct the irreversible equations of SM from the underlying microdynamics. Yet this framework uses coarse-graining, a procedure that has faced much criticism. I focus on two objections in the literature: claims that coarse-graining makes time-asymmetry (i) 'illusory' and (ii) 'anthropocentric'. I argue that these objections arise from an unsatisfactory justification of coarse-graining prevalent in the literature, rather than from coarse-graining itself. This justification relies on the idea of measurement imprecision. By considering the role that abstraction and autonomy play, I provide an alternative justification and offer replies to the illusory and anthropocentric objections. Finally, I consider the broader consequences of this alternative justification: the connection to debates about inter-theoretic reduction and the implication that the time-asymmetry in SM is weakly emergent. 1Introduction 1.1Prospectus2The Zwanzig-Zeh-Wallace Framework3Why Does This Method Work? 3.1The special conditions account3.2When is a density forwards-compatible?4Anthropocentrism and Illusion: Two Objections 4.1The two objections in more detail4.2Against the justification by measurement imprecision5An Alternative Justification 5.1Abstraction and autonomy5.2An illustration: the Game of Life6Reply to Illusory7Reply to Anthropocentric8The Wider Landscape: Concluding Remarks 8.1Inter-theoretic relations8.2The nature of irreversibility.

Since its introduction, multivariate pattern analysis (MVPA), or 'neural decoding', has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder's dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis?2.2The informational benefits of multivariate pattern analysis3Why the Decoder's Dictum Is False 3.1We don't know what information is decoded3.2The theoretical basis for the dictum3.3Undermining the theoretical basis4Objections and Replies 4.1Does anyone really believe the dictum?4.2Good decoding is not enough4.3Predicting behaviour is not enough5Moving beyond the Dictum6Conclusion.

Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders' and receivers' use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. 1 Introduction 2 Modelling Framework 3 Two Kinds of Content  3.1 Informational content  3.2 Functional content 4 Cases  4.1 Case 1: Simplest case  4.2 Case 2: Partial pooling  4.3 Case 3: Bottleneck  4.4 Case 4: Partial common interest  4.5 Case 5: Deception  4.6 Case 6: A further problem arising from divergent interests 5 Discussion Appendix .

This article argues that common intuitions regarding (a) the specialness of 'use-novel' data for confirmation and (b) that this specialness implies the 'no-double-counting rule', which says that data used in 'constructing' (calibrating) a model cannot also play a role in confirming the model's predictions, are too crude. The intuitions in question are pertinent in all the sciences, but we appeal to a climate science case study to illustrate what is at stake. Our strategy is to analyse the intuitive claims in light of prominent accounts of confirmation of model predictions. We show that on the Bayesian account of confirmation, and also on the standard classical hypothesis-testing account, claims (a) and (b) are not generally true; but for some select cases, it is possible to distinguish data used for calibration from use-novel data, where only the latter confirm. The more specialized classical model-selection methods, on the other hand, uphold a nuanced version of claim (a), but this comes apart from (b), which must be rejected in favour of a more refined account of the relationship between calibration and confirmation. Thus, depending on the framework of confirmation, either the scope or the simplicity of the intuitive position must be revised. 1 Introduction2 A Climate Case Study3 The Bayesian Method vis-à-vis Intuitions4 Classical Tests vis-à-vis Intuitions5 Classical Model-Selection Methods vis-à-vis Intuitions  5.1 Introducing classical model-selection methods  5.2 Two cases6 Re-examining Our Case Study7 Conclusion.

Non-Archimedean probability functions allow us to combine regularity with perfect additivity. We discuss the philosophical motivation for a particular choice of axioms for a non-Archimedean probability theory and answer some philosophical objections that have been raised against infinitesimal probabilities in general. 1 Introduction2 The Limits of Classical Probability Theory  2.1 Classical probability functions  2.2 Limitations  2.3 Infinitesimals to the rescue?3 NAP Theory  3.1 First four axioms of NAP  3.2 Continuity and conditional probability  3.3 The final axiom of NAP  3.4 Infinite sums  3.5 Definition of NAP functions via infinite sums  3.6 Relation to numerosity theory4 Objections and Replies  4.1 Cantor and the Archimedean property  4.2 Ticket missing from an infinite lottery  4.3 Williamson's infinite sequence of coin tosses  4.4 Point sets on a circle  4.5 Easwaran and Pruss5 Dividends  5.1 Measure and utility  5.2 Regularity and uniformity  5.3 Credence and chance  5.4 Conditional probability6 General Considerations  6.1 Non-uniqueness  6.2 InvarianceAppendix .