Lawyers and judges in the early American republic were surprisingly reluctant to penalise colleagues for malpractice and misconduct towards clients. Though they were part of a legal culture obsessed with preserving lawyers’ moral rectitude, they nonetheless remained sceptical of attempts to address malpractice. This article explores that apparent contradiction. I analyse allegedly wronged clients’ unsuccessful attempts to seek legal satisfaction, whether in civil, criminal, or professional suspension proceedings. I find that the period’s public-spirited legal ethics was in fact a major (...) contributor to these former clients’ difficulties. Legal reformers worried constantly about the dangers to the republic of too-zealous advocacy, which might undermine the public interest. These concerns helped render the opposite problem – of lazy or even duplicitous client ‘advocacy’ – invisible and irremediable. Stories from the past, I argue, help illuminate a tendency to overlook malpractice that continues to this day. (shrink)

This paper examines the relationship between simulation and experiment. Many discussions of simulation, and indeed the term "numerical experiments," invoke a strong metaphor of experimentation. On the other hand, many simulations begin as attempts to apply scientific theories. This has lead many to characterize simulation as lying between theory and experiment. The aim of the paper is to try to reconcile these two points of viewto understand what methodological and epistemological features simulation has in common with experimentation, while at the (...) same time keeping a keen eye on simulation's ancestry as a form of scientific theorizing. In so doing, it seeks to apply some of the insights of recent work on the philosophy of experiment to an aspect of theorizing that is of growing philosophical interest: the construction of local models. (shrink)

Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a “number crunching” technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories and more (...) emphasis on the role of theory in guiding the construction of models. (shrink)

The Ethics of Need: Agency, Dignity, and Obligation argues for the philosophical importance of the notion of need and for an ethical framework through which we can determine which needs have moral significance. In the volume, Sarah Clark Miller synthesizes insights from Kantian and feminist care ethics to establish that our mutual and inevitable interdependence gives rise to a duty to care for the needs of others. Further, she argues that we are obligated not merely to meet others’ needs (...) but to do so in a manner that expresses "dignifying care," a concept that captures how human interactions can grant or deny equal moral standing and inclusion in a moral community. She illuminates these theoretical developments by examining two cases where urgent needs require a caring and dignifying response: the needs of the elderly and the needs of global strangers. Those working in the areas of feminist theory, women’s studies, aging studies, bioethics, and global studies should find this volume of interest. (shrink)

Statistical mechanics involves probabilities. At the same time, most approaches to the foundations of statistical mechanics--programs whose goal is to understand the macroscopic laws of thermal physics from the point of view of microphysics--are classical; they begin with the assumption that the underlying dynamical laws that govern the microscopic furniture of the world are deterministic. This raises some potential puzzles about the proper interpretation of these probabilities.

This Element introduces the philosophical literature on models, with an emphasis on normative considerations relevant to models for decision-making. Chapter 1 gives an overview of core questions in the philosophy of modeling. Chapter 2 examines the concept of model adequacy for purpose, using three examples of models from the atmospheric sciences to describe how this sort of adequacy is determined in practice. Chapter 3 explores the significance of using models that are not adequate for purpose, including the purpose of informing (...) public decisions. Chapter 4 provides a basic framework for values in modelling, using a case study to highlight the ethical challenges in building models for decision making. It concludes by establishing the need for strategies to manage value judgments in modelling, including the potential for public participation in the process. (shrink)

Introduction -- Sanctioning models : theories and their scope -- Methodology for a virtual world -- A tale of two methods -- When theories shake hands -- Models of climate : values and uncertainties -- Reliability without truth -- Conclusion.

An assessment of America's preference for "extra-large" shares examples ranging from mega churches and breast augmentation to landfills and mega-malls, in a cautionary report that reveals some of the consequences of these choices.

There continues to be a vigorous public debate in our society about the status of climate science. Much of the skepticism voiced in this debate suffers from a lack of understanding of how the science works - in particular the complex interdisciplinary scientific modeling activities such as those which are at the heart of climate science. In this book Eric Winsberg shows clearly and accessibly how philosophy of science can contribute to our understanding of climate science, and how it (...) can also shape climate policy debates and provide a starting point for research. Covering a wide range of topics including the nature of scientific data, modeling, and simulation, his book provides a detailed guide for those willing to look beyond ideological proclamations, and enriches our understanding of how climate science relates to important concepts such as chaos, unpredictability, and the extent of what we know. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

Simulations (both digital and analog) and experiments share many features. But what essential features distinguish them? I discuss two proposals in the literature. On one proposal, experiments investigate nature directly, while simulations merely investigate models. On another proposal, simulations differ from experiments in that simulationists manipulate objects that bear only a formal (rather than material) similarity to the targets of their investigations. Both of these proposals are rejected. I argue that simulations fundamentally differ from experiments with regard to the background (...) knowledge that is invoked to argue for the “external validity” of the investigation. (shrink)

Sovereign is he who provides the exception.…The exception is more interesting than the rule. The rule proves nothing; the exception proves everything. In the exception the power of real life breaks through the crust of a mechanism that has become torpid by repetition.In spring 2020, in response to the COVID-19 crisis, world leaders imposed severe restrictions on citizens’ civil, political, and economic liberties. These restrictions went beyond less controversial and less demanding social distancing measures seen in past epidemics. Many states (...) and countries imposed universal lockdowns. Lockdowns, as we define them here, require people to stay home; in some countries and places, citizens must have ad hoc licenses to... (shrink)

Over the last several years, there has been an explosion of interest and attention devoted to the problem of Uncertainty Quantification (UQ) in climate science—that is, to giving quantitative estimates of the degree of uncertainty associated with the predictions of global and regional climate models. The technical challenges associated with this project are formidable, and so the statistical community has understandably devoted itself primarily to overcoming them. But even as these technical challenges are being met, a number of persistent conceptual (...) difficulties remain. So why is UQ so important in climate science? UQ, I would like to argue, is first and foremost a tool for communicating knowledge from experts to policy makers in a way that is meant to be free from the influence of social and ethical values. But the standard ways of using probabilities to separate ethical and social values from scientific practice cannot be applied in a great deal of climate modeling, because the roles of values in creating the models cannot be discerned after the fact—the models are too complex and the result of too much distributed epistemic labor. I argue, therefore, that typical approaches for handling ethical/social values in science do not work well here. (shrink)

Using an example of a computer simulation of the convective structure of a red giant star, this paper argues that simulation is a rich inferential process, and not simply a "number crunching" technique. The scientific practice of simulation, moreover, poses some interesting and challenging epistemological and methodological issues for the philosophy of science. I will also argue that these challenges would be best addressed by a philosophy of science that places less emphasis on the representational capacity of theories (and ascribes (...) that capacity instead to models) and more emphasis on the role of theory in guiding (rather than determining) the construction of models. (shrink)

Background Researchers are required to determine whether a person has capacity to consent to a research study before they are able to participate. The Mental Capacity Act and accompanying Code of Practice for England and Wales provide some guidance on this process, but researchers have identified that it can be difficult to determine capacity to consent when a person has complex cognitive or communication needs. This study aimed to understand the experiences and opinions of researchers who recruit people with dementia (...) to research projects, to inform the future development of training resources. Methods A mixed method, cross-sectional, electronic survey was circulated via social media and research networks in England and Wales. The survey remained open for ten weeks and included open and closed questions exploring respondents’ confidence in determining capacity in the context of recruiting people with dementia to consent, their views on training and support they have experienced and their suggestions for future training and support needs. Results 60 respondents completed the survey from across England and Wales. Although 75% of respondents had experience of determining capacity to consent with people with dementia to research, only 13% rated themselves as feeling ‘very confident’ in this. Qualitative content analysis of open responses led to the generation of six themes, explaining researchers’ confidence, competence and future training needs in this area: (1) Researcher uncertainties, (2) Lack of time, (3) Balancing information complexity with accessibility, (4) Gatekeepers, (5) Existing enablers and (6) Envisioning future training. Conclusions Researchers would benefit from specific training in undertaking conversations around consent with people with dementia. People with dementia may have fluctuating capacity, and despite support from caregivers, researchers have little practical guidance on methods of determining a person’s ability to understand or appreciate the information they have provided during the consent process. Given the development of large complex trials within dementia research, there is an urgency to develop specific and practical guidance and training for researchers working with people with dementia and their families. (shrink)

This paper discusses a crisis of accountability that arises when scientific collaborations are massively epistemically distributed. We argue that social models of epistemic collaboration, which are social analogs to what Patrick Suppes called a “model of the experiment,” must play a role in creating accountability in these contexts. We also argue that these social models must accommodate the fact that the various agents in a collaborative project often have ineliminable, messy, and conflicting interests and values; any story about accountability in (...) a massively distributed collaboration must therefore involve models of such interests and values and their methodological and epistemic effects. (shrink)

In the philosophy of climate science, debate surrounding the issue of variety of evidence has mostly taken the form of attempting to connect these issues in climate science and climate modeling with philosophical accounts of what has come to be known as “robustness analysis.” I argue that an “explanatory” conception of robustness is the best candidate for understanding variety of evidence in climate science. I apply the analysis to both examples of model agreement, as well at to the convergence of (...) evidence from both model and non-model sources. (shrink)

In his recent book, Time and Chance, David Albert claims that by positing that there is a uniform probability distribution defined, on the standard measure, over the space of microscopic states that are compatible with both the current macrocondition of the world, and with what he calls the “past hypothesis”, we can explain the time asymmetry of all of the thermodynamic behavior in the world. The principal purpose of this paper is to dispute this claim. I argue that Albert's proposal (...) fails in his stated goal—to show how to use the time‐reversible dynamics of Newtonian physics to “underwrite the actual content of our thermodynamic experience” (Albert 2000, 159). Albert's proposal can satisfactorily explain why the overall entropy of the universe as a whole is increasing, but it does not and cannot explain the increasing entropy of relatively small, relatively short‐lived systems in energetic isolation without making use of a principle that leads to reversibility objections. (shrink)

There are a variety of topics in the philosophy of science that need to be rethought, in varying degrees, after one pays careful attention to the ways in which computer simulations are used in the sciences. There are a number of conceptual issues internal to the practice of computer simulation that can benefit from the attention of philosophers. This essay surveys some of the recent literature on simulation from the perspective of the philosophy of science and argues that philosophers have (...) a lot to learn by paying closer attention to the practice of simulation. (shrink)

In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model comes not only (...) from the credentials supplied to it by the governing theory, but also from the antecedently established credentials of the model building techniques employed by the simulationists. In other words, there are certain sorts of model building techniques which are taken, in and of themselves, to be reliable. Some of these model building techniques, moreover, incorporate what are sometimes called “falsifications.” These are contrary-to-fact principles that are included in a simulation model and whose inclusion is taken to increase the reliability of the results. The example of a falsification that I consider, called artificial viscosity, is in widespread use in computational fluid dynamics. Artificial viscosity, I argue, is a principle that is successfully and reliably used across a wide domain of fluid dynamical applications, but it does not offer even an approximately “realistic” or true account of fluids. Artificial viscosity, therefore, is a counter-example to the principle that success implies truth – a principle at the foundation of scientific realism. It is an example of reliability without truth. (shrink)

Scientific modelling is a value-laden process: the decisions involved can seldom be made using ‘scientific’ criteria alone, but rather draw on social and ethical values. In this paper, we draw on a body of philosophical literature to analyze a COVID-19 vaccination model, presenting a case study of social and ethical value judgments in health-oriented modelling. This case study urges us to make value judgments in health-oriented models explicit and interpretable by non-experts and to invite public involvement in making them.

A collection of newly commissioned papers on themes from David Albert's Time and Chance (HUP, 2000), with replies by Albert. Introduction [Barry Loewer, Brad Weslake, and Eric Winsberg] I. Overview of Time and Chance 1. The Mentaculus: A Probability Map of the Universe [Barry Loewer] II. Philosophical Foundations 2. The Metaphysical Foundations of Statistical Mechanics: On the Status of PROB and PH [Eric Winsberg] 3. The Logic of the Past Hypothesis [David Wallace] 4. In What Sense Is the (...) Early Universe Fine-Tuned? [Sean M. Carroll] 5. The Meta-Reversibility Objection [Christopher J. G. Meacham] 6. Typicality versus Humean Probabilities as the Foundation of Statistical Mechanics [Dustin Lazarovici] 7. The Past Hypothesis and the Nature of Physical Laws [Eddy Keming Chen] 8. On the Albertian Demon [Tim Maudlin] III. Underwriting the Asymmetries of Knowledge and Intervention 9. Reading the Past in the Present [Nick Huggett] 10. Causes, Randomness, and the Past Hypothesis [Mathias Frisch] 11. Time, Flies, and Why We Can’t Control the Past [Alison Fernandes] 12. The Concept of Intervention in Time and Chance [Sidney Felder] Conclusion [David Albert]. (shrink)

In this paper, we explore the extent to which issues of simulation model validation take on novel characteristics when the models in question become particularly complex. Our central claim is that complex simulation models in general, and global models of climate in particular, face a form of confirmation holism. This holism, moreover, makes analytic understanding of complex models of climate either extremely difficult or even impossible. We argue that this supports a position we call convergence skepticism: the belief that the (...) existence of a plurality of different models making a plurality of different forecasts of future climate is likely to be a persistent feature of global climate science. (shrink)

1. Introduction; Elisabeth A. Lloyd and Eric Winsberg.- Section 1: Confirmation and Evidence.- 2. The Scientific Consensus on Climate Change: How Do We Know We’re Not Wrong?; Naomi Oreskes.- 3. Satellite Data and Climate Models Redux.- 3a. Introduction to Chapter 3: Satellite Data and Climate Models; Elisabeth A. Lloyd.- Ch. 3b Fact Sheet to "Consistency of Modelled and Observed Temperature Trends in the Tropical Troposphere"; Benjamin D. Santer et al..- Ch. 3c Reprint of "Consistency of Modelled and Observed Temperature (...) Trends in the Tropical Troposphere"; Benjamin D. Santer et al..- 4. The Role of ’Complex’ Empiricism in the Debates about Satellite Data and Climate Models; Elisabeth A. Lloyd.- 5. Reconciling Climate Model/Data Discrepancies: The Case of the Trees That Didn’t Bark; Michael Mann.- 6. Downscaling of Climate Information; Linda O. Mearns et al..- Section 2: Uncertainties and Robustness.- 7. The Significance of Robust Model Projections; Wendy S. Parker.- 8. Building Trust, Removing Doubt? Robustness Analysis and Climate Modeling; Jay Odenbaugh.- Section 3: Climate Models as Guides to Policy.- 9. Climate Model Confirmation: From Philosophy to Predicting Climate in the Real World; Reto Knutti.- 10. Uncertainty in Climate Science and Climate Policy; Jonathan Rougier and Michel Crucifix.- 11. Communicating Uncertainty to Policy Makers: The Ineliminable Role of Values; Eric Winsberg.- 12. Modeling Climate Policies: A Critical Look at Integrated Assessment Models; Mathias Frisch.- 13. Modelling Mitigation and Adaptation Policies to Predict their Effectiveness: The Limits of Randomized Controlled Trials; Alexandre Marcellesi and Nancy D. Cartwright. (shrink)

Should philosophers of science be paying attention to developments in "nanoscience"? Undoubtedly, it is too early to tell for sure. The goal of this paper is to take a preliminary look. In particular, I look at the use of computational models in the study of nano-sized solid-state materials. What I find is that there are features of these models that appear on their face to be at odds with some basic philosophical intuitions about the relationships between different theories and between (...) theories and their models. My conclusion is that developments in nanoscience are not an unlikely place for novel insights in the philosophy of science to emerge. (shrink)

In a large and impressive body of published work, Quayshawn Spencer has meticulously articulated and defended a metaphysical project aimed at resuscitating a biological conception of race—one free from many of the pitfalls of biological essentialism. If successful, such a project would be highly rewarding, since it would provide a compelling response to philosophers who have denied the genuine existence of race while avoiding the very dangers that they sought to avoid. The aim of this paper is to subject those (...) moves to careful scrutiny and thereby appraise the prospects for a new biologism about race. (shrink)

Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. In this book, Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your .4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, (...) but of probabilistic contents. -/- The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other. (shrink)

Introduction: The humanities enrich and transform the practice of medicine. What remains to be seen, however, is how best to integrate humanities into the medical curriculum to optimize both educational and patient-related outcomes. The present study considers the structure of an innovative student-driven humanities curriculum and seeks to understand its strengths and limitations, as well as make recommendations for improvement. Methods: The Penn State College of Medicine, University Park Regional Campus uses an inquiry-based approach to education, whereby students are responsible (...) for creating learning objectives in four core pillars of exploration: Foundational Science, Clinical Science, Health Systems Science, and Health Humanities. This study explores student-derived humanities learning objectives (HLO) across four years of the curriculum. Results: 420 HLOs met criteria for analysis and were coded as instrumental (developing direct clinical skill), non-instrumental (non-skill based), or both. Of these, 125 (30%) were instrumental, 239 (57%) were non-instrumental, and 56 (13%) were coded as both. Most instrumental HLO centered around communication skills. Non-instrumental HLO most commonly focused on bearing witness and critiquing a particular experience within a social and/or political context. Conclusions: Findings from this study contribute to the development of a humanities curriculum in a student-directed learning program. Non-instrumental HLO lacked a theoretical framework to guide student’s investigations to a deeper level of analysis. Student-directed learning offers many strengths, but can be enhanced through external direction from humanities trained faculty, particularly given that many medical students have a limited humanities background. (shrink)

Existing discussions of legal proof address a host of apparently disparate questions: What does it take to prove a fact beyond a reasonable doubt? Why is the reasonable doubt standard notoriously elusive, sometimes considered by courts to be impossible to define? Can the standard of proof by a preponderance of the evidence be defined in terms of probability thresholds? Why is statistical evidence often insufficient to meet the burden of proof? -/- This paper defends an account of proof that addresses (...) each of these questions. Where existing theories take a piecemeal approach to these puzzles, my theory develops an insight that unifies them—namely, the thesis that legal proof requires knowledge. Although this thesis may seem radical at first, I answer several common objections to it, and I argue that it does better than several competing accounts when it comes to making sense of our intuitions about what legal proof requires. (shrink)

This paper motivates and develops a novel semantics for several epistemic expressions, including possibility modals and indicative conditionals. The semantics I defend constitutes an alternative to standard truth conditional theories, as it assigns sets of probability spaces as sentential semantic values. I argue that what my theory lacks in conservatism is made up for by its strength. In particular, my semantics accounts for the distinctive behavior of nested epistemic modals, indicative conditionals embedded under probability operators, and instances of constructive dilemma (...) containing epistemic vocabulary. (shrink)

Violations of the Bell inequalities in EPR-Bohm type experiments have set the literature on the metaphysics of microscopic systems to flirting with some sort of metaphysical holism regarding spatially separated, entangled systems. The rationale for this behavior comes in two parts. The first part relies on the proof, due to Jon Jarrett [2] that the experimentally observed violations of the Bell inequalities entail violations of the conjunction of two probabilistic constraints. Jarrett called these two constraints locality and completeness. We prefer (...) the terminology of locality and factorizability.[3] The first part of the rationale for metaphysical holism urges that only Jarrett’s locality allows for “peaceful coexistence” between any model of EPR-Bohm type experiments and special relativity. Factorizability, it is suggested, must be jettisoned. (shrink)

Statistical Mechanics (SM) involves probabilities. At the same time, most approaches to the foundations of SM—programs whose goal is to understand the macroscopic laws of thermal physics from the point of view of microphysics—are classical; they begin with the assumption that the underlying dynamical laws that govern the microscopic furniture of the world are (or can without loss of generality be treated as) deterministic. This raises some potential puzzles about the proper interpretation of these probabilities. It also raises, more generally, (...) the question of what kinds, if any, of objective probabilities can exist in a deterministic world. (shrink)

Roman Frigg and others have developed a general epistemological argument designed to cast doubt on the capacity of a broad range of mathematical models to generate “decision relevant predictions.” In this article, we lay out the structure of their argument—an argument by analogy—with an eye to identifying points at which certain epistemically significant distinctions might limit the force of the analogy. Finally, some of these epistemically significant distinctions are introduced and defended as relevant to a great many of the predictive (...) mathematical modeling projects employed in contemporary climate science. (shrink)

This paper argues that just as full beliefs can constitute knowledge, so can properties of your credence distribution. The resulting notion of probabilistic knowledge helps us give a natural account of knowledge ascriptions embedding language of subjective uncertainty, and a simple diagnosis of probabilistic analogs of Gettier cases. Just like propositional knowledge, probabilistic knowledge is factive, safe, and sensitive. And it helps us build knowledge-based norms of action without accepting implausible semantic assumptions or endorsing the claim that knowledge is interest-relative.

Traditionally, discussions of moral participation – and in particular moral agency – have focused on fully formed human actors. There has been some interest in the development of morality in humans, as well as interest in cultural differences when it comes to moral practices, commitments, and actions. However, until relatively recently, there has been little focus on the possibility that nonhuman animals have any role to play in morality, save being the objects of moral concern. Moreover, when nonhuman cases are (...) considered as evidence of moral agency or subjecthood, there has been an anthropocentric tendency to focus on those behaviors that inform our attributions of moral agency to humans. For example, some argue that the ability to evaluate the principles upon which a moral norm is grounded is required for full moral agency. Certainly, if a moral agent must understand what makes an action right or wrong, then most nonhuman animals would not qualify (and perhaps some humans too). However, if we are to understand the evolution of moral psychology and moral practice, we need to turn our attention to the foundations of full moral agency. We must first pay attention to the more broadly normative practices of other animals. Here, we begin that project by considering evidence that great apes and cetaceans participate in normative practices. (shrink)

Suppose some person 'A' sets out to accomplish a difficult, long-term goal such as writing a passable Ph.D. thesis. What should you believe about whether A will succeed? The default answer is that you should believe whatever the total accessible evidence concerning A's abilities, circumstances, capacity for self-discipline, and so forth supports. But could it be that what you should believe depends in part on the relationship you have with A? We argue that it does, in the case where A (...) is yourself. The capacity for "grit" involves a kind of epistemic resilience in the face of evidence suggesting that one might fail, and this makes it rational to respond to the relevant evidence differently when you are the agent in question. We then explore whether similar arguments extend to the case of "believing in" our significant others -- our friends, lovers, family members, colleagues, patients, and students. (shrink)

This paper explores some connections between competing conceptions of scientific laws on the one hand, and a problem in the foundations of statistical mechanics on the other. I examine two proposals for understanding the time asymmetry of thermodynamic phenomenal: David Albert's recent proposal and a proposal that I outline based on Hans Reichenbach's “branch systems”. I sketch an argument against the former, and mount a defense of the latter by showing how to accommodate statistical mechanics to recent developments in the (...) philosophy of scientific laws. (shrink)

We call attention to an underappreciated way in which non-epistemic values influence evidence evaluation in science. Our argument draws upon some well-known features of scientific modeling. We show that, when scientific models stand in for background knowledge in Bayesian and other probabilistic methods for evidence evaluation, conclusions can be influenced by the non-epistemic values that shaped the setting of priorities in model development. Moreover, it is often infeasible to correct for this influence. We further suggest that, while this value influence (...) is not particularly prone to the problem of wishful thinking, it could have problematic non-epistemic consequences in some cases. (shrink)

This paper defends an account of full belief, including an account of its relationship to credence. Along the way, I address several familiar and difficult questions about belief. Does fully believing a proposition require having maximal confidence in it? Are rational beliefs closed under entailment, or does the preface paradox show that rational agents can believe inconsistent propositions? Does whether you believe a proposition depend partly on your practical interests? My account of belief resolves the tension between conflicting answers to (...) these questions that have been defended in the literature. In addition, my account complements fruitful probabilistic theories of assertion and knowledge. (shrink)