Evidence, Misc

The essays in this volume address three fundamental questions in the philosophy of science: What is required for some fact to be evidence for a scientific ...

Recently in this journal Sherrilyn Roush (2004) defends positive relevance as a necessary (albeit not a sufficient) condition for evidence by rejecting two of the counterexamples from my earlier (2001) work. In this reply I argue that Roush's critique is not successful.

What is required for something to be evidence for a hypothesis? In this fascinating, elegantly written work, distinguished philosopher of science Peter Achinstein explores this question, rejecting typical philosophical and statistical theories of evidence. He claims these theories are much too weak to give scientists what they want--a good reason to believe--and, in some cases, they furnish concepts that mistakenly make all evidential claims a priori. Achinstein introduces four concepts of evidence, defines three of them by reference to "potential" evidence, (...) and characterizes the latter using a novel epistemic interpretation of probability. The resulting theory is then applied to philosophical and historical issues. Solutions are provided to the "grue," "ravens," "lottery," and "old-evidence" paradoxes, and to a series of questions. These include whether explanations or predictions furnish more evidential weight, whether individual hypotheses or entire theoretical systems can receive evidential support, what counts as a scientific discovery, and what sort of evidence is required for it. The historical questions include whether Jean Perrin had non-circular evidence for the existence of molecules, what type of evidence J. J. Thomson offered for the existence of the electron, and whether, as is usually supposed, he really discovered the electron. Achinstein proposes answers in terms of the concepts of evidence introduced. As the premier book in the fabulous new series Oxford Studies in Philosophy of Science, this volume is essential for philosophers of science and historians of science, as well as for statisticians, scientists with philosophical interests, and anyone curious about scientific reasoning. (shrink)

An a priori thesis about evidence, defended by many, states that the only empirical fact that can affect the truth of an objective evidence claim of the form ‘e is evidence for h’ (or ‘e confirms h to degree r’) is the truth of e; all other considerations are a priori. By examining cases involving evidential flaws, I challange this claim and defend an empirical concept of evidence. In accordance with such a concept, whether, and the extent to which, e, (...) if true, confirms h is an empirical, not a priori, fact. (shrink)

According to a standard account of evidence, one piece of information is stronger evidence for an hypothesis than is another iff the probability of the hypothesis on the one is greater than it is on the other. This condition, I argue, is neither necessary nor sufficient because various factors can strengthen the evidence for an hypothesis without increasing (and even decreasing) its probability. Contrary to what probabilists claim, I show that this obtains even if a probability function can take these (...) evidential factors into account in ways they suggest and yield a unique probability value. Nor will the problem be solved by appealing to second-order probabilities. (shrink)

I present here a case against the evidentialist approach that claims that in so far as our interests are epistemic what should guide our belief formation and revision is always a strict adherence to the available evidence. I go on to make the stronger claim that some beliefs based on admittedly “insufficient” evidence may exhibit epistemic virtue. I propose that we consider a form of courage to be an intellectual or epistemic virtue. It is through this notion of courage that (...) we can see a weakness in the evidentialist position. Adopting a doxastically courageous approach allows us to acknowledge the role that evidence has in epistemic justification and its connection with promoting epistemic value, but it avoids the narrowness of an evidentialist position. The epistemically courageous agent is not one who disregards the evidence entirely, but she also realizes that taking risks will not necessarily keep her from her epistemic goals. Believing something in the face of insufficient evidence is not always an epistemic vice to be avoided, and the agent that recognizes this is better off for it. (shrink)

If the problem of induction were soluble, it should be solved inductively: by observing how scientists observe, etc. The fact is that scientific research is successful, and the real question is, will it be so in future? If there is a formula of induction by which success is achieved, then by this formula we can say, as long as it will be used science will succeed. If there is no formula it looks as if future success in scientific research is (...) most doubtful. Hence, a transcendental argument for induction goes, there is an inductive formula. Since, however, such a view of induction is rejected even by inductivists as naive, the argument collapses. Hence the question is, on what basis do we project the future success of science? My answer is that this future success is built into our social institutions and is partially institutionally safeguarded. (shrink)

Good’s theorem is the apparent platitude that it is always rational to ‘look before you leap’: to gather information before making a decision when doing so is free. We argue that Good’s theorem is not platitudinous and may be false. And we argue that the correct advice is rather to ‘make your act depend on the answer to a question’. Looking before you leap is rational when, but only when, it is a way to do this.

How is the burden of proof to be distributed among individuals who are involved in resolving a particular issue? Under what conditions should the burden of proof be distributed unevenly? We distinguish attitudinal from dialectical burdens and argue that these questions should be answered differently, depending on which is in play. One has an attitudinal burden with respect to some proposition when one is required to possess sufficient evidence for it. One has a dialectical burden with respect to some proposition (...) when one is required to provide supporting arguments for it as part of a deliberative process. We show that the attitudinal burden with respect to certain propositions is unevenly distributed in some deliberative contexts, but in all of these contexts, establishing the degree of support for the proposition is merely a means to some other deliberative end, such as action guidance, or persuasion. By contrast, uneven distributions of the dialectical burden regularly further the aims of deliberation, even in contexts where the quest for truth is the sole deliberative aim, rather than merely a means to some different deliberative end. We argue that our distinction between these two burdens resolves puzzles about unevenness that have been raised in the literature. (shrink)

Two theses figure centrally in work on the epistemology of disagreement: Equal Weight (‘EW’) and Uniqueness (‘U’). According to EW, you should give precisely as much weight to the attitude of a disagreeing epistemic peer as you give to your own attitude. U has it that, for any given proposition and total body of evidence, some doxastic attitude is the one the evidence makes rational (justifies) toward that proposition. Although EW has received considerable discussion, the case for U has not (...) been critically evaluated. Endorsing U, we argue, commits one to the highly controversial thesis that whatever fixes your rational attitudes can do so only by fixing what evidence you have. This commitment imposes a relatively demanding requirement on justified belief in U, one that we argue is not satisfied by what is currently the strongest available case for U, due to Roger White [2005]. Our challenge to U makes more trouble for its proponents than do the worries about U expressed by Gideon Rosen [2001] and Thomas Kelly [2010]. Moreover, if Kelly [2010] is correct in thinking that EW “carries with it a commitment to” U—a claim which we accept for reasons similar to Kelly’s but is beyond this paper’s scope (but see Ballantyne and Coffman [forthcoming])—then our challenge to U bears importantly on EW: to the extent that our challenge to U succeeds, EW also suffers. (shrink)

Sherrilyn Roush's Tracking Truth provides a sustained and ambitious development of the basic idea that knowledge is true belief that tracks the truth. In this essay, I provide a quick synopsis of Roush's book and offer a substantive discussion of her analysis of scientific evidence. Roush argues that, for e to serve as evidence for h, it should be easier to determine the truth value of e than it is to determine the truth value of h, an ideal she refers (...) to as 'leverage'. She defends a detailed method by which the value of p(h/e) is computed without 'direct' information about p(h) but only using evidence about the value of p(e), from which the value of p(h) is derived. She presents an example of how to use her leverage method, which I argue involves a certain critical mistake. I show how the leveraging method can be used in a way that is sound--I conclude with a few remarks about the importance of distinguishing clearly between prior and posterior probabilities. (shrink)

Higher-order evidence is, roughly, evidence of evidence. The idea is that evidence comes in levels. At the first, or lowest, evidential level is evidence of the familiar type—evidence concerning some proposition that is not itself about evidence. At a higher evidential level the evidence concerns some proposition about the evidence at a lower level. Only in relatively recent years has this less familiar type of evidence been explicitly identified as a subject of epistemological focus, and the work on it remains (...) relegated to a small circle of authors and a short stack of published articles—far disproportionate to the attention it deserves. It deserves to occupy center stage for several reasons. First, higher-order evidence frequently arises in a strikingly diverse range of epistemic contexts, including testimony, disagreement, empirical observation, introspection, and memory, among others. Second, in many of the contexts in which it arises, such evidence plays a crucial epistemic role. Third, the precise role it plays is complex, gives rise to a number of interesting epistemological puzzles, and for these reasons remains controversial and is not yet fully understood. As such, higher-order evidence merits systematic investigation. This thesis undertakes such an investigation. It aims to produce a thorough account of higher-order evidence—what it is, how it works, and its epistemic consequences. Chapter 1 serves as a general introduction to the topic and an overview of the existing literature, but primarily aims to further elucidate the concept of higher-order evidence and build a theoretical framework for later chapters. Chapter 2 develops an account of what I call “higher-order support”: the bearing higher-order evidence has, not on corresponding “lower-order evidence” (roughly, the evidence the higher-order evidence is about), but on corresponding “object-level propositions” (roughly, the propositions the higher-order evidence alleges the lower-order evidence to be about). Chapter 3 develops an account of “levels interaction”: the effect on overall support when the different evidential levels combine. Chapter 4 identifies important consequences of the theoretical results of the previous two chapters and applies the theory to four select cases of current epistemological controversy—testimony, memory, the closure of inquiry, and disagreement. (shrink)

INTRODUCTION I should begin by warning the reader that many of the views presented in this book are decidedly unfashionable; the theory of probability I ...

Science advances by means of argument and debate. Based on a formal model of complex argumentation, this article assesses the interplay between evidential and inferential drivers in scientific controversy, and explains, in particular, why both evidence accumulation and argumentation are veritistically valuable. By improving the conditions for applying veritistic indicators , novel evidence and arguments allow us to distinguish true from false hypotheses more reliably. Because such veritistic indicators also underpin inductive reasoning, evidence accumulation and argumentation enhance the reliability of (...) inductive inference, for example, inference to the best explanation. 1 Introduction2 Theory of Dialectical Structures3 Debate Simulations4 From Evidence and Arguments to Truth: The First Route5 From Evidence to Truth: The Second Route6 Conclusion. (shrink)

Evidence is often taken to be foundational, in that while other propositions may be inferred from our evidence, evidence propositions are themselves not inferred from anything. I argue that this conception is false, since the non-inferential propositions on which beliefs are ultimately founded may be forgotten or undermined in the course of enquiry.

Rowbottom (2008) has recently challenged my definition of epistemic reasons for action and has offered an alternative account. In this paper, I argue that less than giving an 'alternative' definition, Rowbottom has offered an additional condition to my original account. I argue, further, that such an extra condition is unnecessary, i.e. that the arguments designed to motivate it do not go through.

In this paper I consider whether there can be such things as epistemic reasons for action. I consider three arguments to the contrary and argue that none are successful, being either somewhat question-begging or too strong by ruling out what most epistemologists think is a necessary feature of epistemic justification, namely the epistemic basing relation. I end by suggesting a "non-cognitivist" model of epistemic reasons that makes room for there being epistemic reasons for action and suggest that this model may (...) support moral realism. (shrink)

Saul Kripke argued that the requirement that knowledge eliminate all possibilities of error leads to dogmatism . According to this view, the dogmatism puzzle arises because of a requirement on knowledge that is too strong. The paper argues that dogmatism can be avoided even if we hold on to the strong requirement on knowledge. I show how the argument for dogmatism can be blocked and I argue that the only other approach to the puzzle in the literature is mistaken.

Probabilistic dependence and independence are among the key concepts of Bayesian epistemology. This paper focuses on the study of one specific quantitative notion of probabilistic dependence. More specifically, section 1 introduces Keynes’s coefficient of dependence and shows how it is related to pivotal aspects of scientific reasoning such as confirmation, coherence, the explanatory and unificatory power of theories, and the diversity of evidence. The intimate connection between Keynes’s coefficient of dependence and scientific reasoning raises the question of how Keynes’s coefficient (...) of dependence is related to truth, and how it can be made fruitful for epistemological considerations. This question is answered in section 2 of the paper. Section 3 outlines the consequences the results have for epistemology and the philosophy of science from a Bayesian point of view. (shrink)

Contemporary ways of understanding of science, especially in the philosophy of science, are beset by overly abstract and formal models of evidence. In such models, the only interesting feature of evidence is that it has a one-way ``support'' relation to hypotheses, theories, causal claims, etc. These models create a variety of practical and philosophical problems, one prominent example being the experimenter's regress. According to the experimenter's regress, good evidence is produced by good techniques, but which techniques are good is only (...) determined by whether they produce the evidence we expect. The best answer to this problem within the traditional approach relies on the concept of robust evidence, but this answer ultimately falls flat because it creates impossible requirements on good evidence. The problem can more easily be solved by rejecting abstract, formalistic models of evidence in favor of a model of inquiry which pays attention to the temporal complexity of the process of inquiry and the distinction between observational and experimental evidence. (shrink)

This paper addresses the question of whether gathering additional evidence is always rationally required, both from the point of view of instrumental rationality and of epistemic rationality. It is shown that in certain situations, it is not instrumentally rational to look for more evidence before making a decision. These are situations in which the risk of “misleading” evidence – a concept that has both instrumental and epistemic senses – is not offset by the gains from the possibility of non-misleading evidence. (...) These situations also undermine a particular argument for the claim that it is epistemically rational to look for more evidence, though it is argued that the relationship between instrumental and epistemic rationality makes such arguments flawed to begin with. Furthermore, these situations show us that our epistemic and our practical goals sometimes point us in different directions, not merely because of our limited resources or because our desires are sometimes best served by being in particular epistemic states, but because of the nature of rational action. (shrink)

One strategy for dealing with apparent cases of knowledge from falsehood is to deny that the knowledge actually is from a falsehood. Those endorsing such a move have suggested that cases of knowledge from falsehood are instead cases of knowledge despite falsehood. We here provide a dilemma for those wanting to reject the possibility of knowledge from falsehood. The dilemma is explained in part by examining recent attempts to deny that knowledge can be inferentially derived from falsehood.

This article agrees with Philip Kitcher that we should aim for a well-ordered science, one that answers the right questions in the right ways. Crucial to this is to address questions of use: Which scientific account is right for which system in which circumstances? This is a difficult question: evidence that may support a scientific claim in one context may not support it in another. Drawing on examples in physics and other sciences, this article argues that work on the warrant (...) of theories in philosophy of science needs to change. Emphasis should move from the warrant of theories in the abstract to questions of evidence for use. (shrink)

WE AIM HERE to outline a theory of evidence for use. More specifically we lay foundations for a guide for the use of evidence in predicting policy effectiveness in situ, a more comprehensive guide than current standard offerings, such as the Maryland rules in criminology, the weight of evidence scheme of the International Agency for Research on Cancer (IARC), or the US ‘What Works Clearinghouse’. The guide itself is meant to be well-grounded but at the same time to give practicable (...) advice, that is, advice that can be used by policy-makers not expert in the natural and social sciences, assuming they are well-intentioned and have a reasonable but limited amount of time and resources available for searching out evidence and deliberating. (shrink)

Sometimes we get evidence of our own epistemic malfunction. This can come from finding out we’re fatigued, or have been drugged, or that other competent and well-informed thinkers disagree with our beliefs. This sort of evidence seems to seems to behave differently from ordinary evidence about the world. In particular, getting such evidence can put agents in a position where the most rational response involves violating some epistemic ideal.

The main appeal of the currently popular "bootstrap" account of confirmation developed by Clark Glymour is that it seems to provide an account of evidential relevance. This account has, however, had severe problems; and Glymour has revised his original account in an attempt to solve them. I argue that this attempt fails completely, and that any similar modifications must also fail. If the problems can be solved, it will only be by radical revisions which involve jettisoning bootstrapping's basic approach to (...) theories. Finally, I argue that there is little reason to think that even such drastic modifications will lead to a satisfactory account of relevance. (shrink)

Among Bayesian confirmation theorists, several quantitative measures of the degree to which an evidential proposition E confirms a hypothesis H have been proposed. According to one popular recent measure, s, the degree to which E confirms H is a function of the equation P(H|E) − P(H|~E). A consequence of s is that when we have two evidential propositions, E1 and E2, such that P(H|E1) = P(H|E2), and P(H|~E1) ≠ P(H|~E2), the confirmation afforded to H by E1 does not equal the (...) confirmation afforded to H by E2. I present several examples that demonstrate the unacceptability of this result, and conclude that we should reject s (and other measures that share this feature) as a measure of confirmation. (shrink)

Michael Devitt ([2006a], [2006b]) argues that, insofar as linguists possess better theories about language than non-linguists, their linguistic intuitions are more reliable. (Culbertson and Gross [2009]) presented empirical evidence contrary to this claim. Devitt ([2010]) replies that, in part because we overemphasize the distinction between acceptability and grammaticality, we misunderstand linguists' claims, fall into inconsistency, and fail to see how our empirical results can be squared with his position. We reply in this note. Inter alia we argue that Devitt's focus (...) on grammaticality intuitions, rather than acceptability intuitions, distances his discussion from actual linguistic practice. We close by questioning a demand that drives his discussion—viz., that, for linguistic intuitions to supply evidence for linguistic theorizing, a better account of why they are evidence is required. (shrink)

Book review of Paul Horwich, Probability and Evidence (Cambridge Philosophy Classics edition), Cambridge: Cambridge University Press, 2016, 147pp, £14.99 (paperback).

Among the most serious challenges to scientific realism are arguments for the underdetermination of theory by evidence. This paper defends a version of scientific realism against what is perhaps the most influential recent argument of this sort, viz. Kyle Stanford’s New Induction over the History of Science. An essential part of the defense consists in a probabilistic analysis of the slogan “absence of evidence is not evidence of absence”. On this basis it is argued that the likelihood of a theory (...) being underdetermined depends crucially on social and historical factors, such as the structure of scientific communities and the time that has passed since the theory first became accepted. This is then shown to serve as the epistemological foundation for a version of scientific realism which avoids Stanford’s New Induction in a principled and non-question-begging way. (shrink)

Consider: -/- The Evidence Question: When, and under what conditions does an agent have proposition E as evidence (at t)? -/- Timothy Williamson's (2000) answer to this question is the well-known E = K thesis: -/- E = K: E is a member of S's evidence set at t iff S knows E at t. -/- I will argue that this answer is inconsistent with the version of Bayesianism that Williamson advocates. This is because E = K allows an agent (...) to garner evidence via inductive inference whereas standard Bayesian views disallow such a thing. Since Williamson's version of Bayesianism shares the key features with the standard Bayesian view, there is an inconsistency. (shrink)

The likelihood theory of evidence (LTE) says, roughly, that all the information relevant to the bearing of data on hypotheses (or models) is contained in the likelihoods. There exist counterexamples in which one can tell which of two hypotheses is true from the full data, but not from the likelihoods alone. These examples suggest that some forms of scientific reasoning, such as the consilience of inductions (Whewell, 1858. In Novum organon renovatum (Part II of the 3rd ed.). The philosophy of (...) the inductive sciences. London: Cass, 1967), cannot be represented within Bayesian and Likelihoodist philosophies of science. (shrink)