Sherrilyn Roush

In her book _Science as Social Knowledge_, Helen Longino argued not only that social values are in fact ineliminable from theory choice in science but also that we ought to rewrite our ideals in such a way as to incorporate this fact. One of the most common criticisms of this idea of granting a legitimate role for social values in theory choice in science is that it just doesn't make sense to regard social preferences as relevant to the truth or to the way things are. According to Susan Haack, what is at issue is whether it is possible to derive an “_is_” from an “_ought_.” One can see that this is not possible, she concludes. Haack does not provide an argument for the view that it is impossible to derive an _is_ from an _ought_, but the intuition she expresses is strong and widespread. This chapter shows that even if we grant this view, we may still consistently believe that social values have a legitimate role in theory choice in science. The chapter defends this conclusion by outlining a view about social values and theory choice that is based on the constructive empiricism (CE) of Bas van Fraassen. It is argued that some questions about what role social values may legitimately play in science look different depending on whether they are viewed from a realist perspective, according to which the aim of science is literally true description of reality, or from the point of view of a constructive empiricist antirealism, according to which the aim of science is empirical adequacy, the fit of a theory to the observables.

I characterize Gettier cases as failures of understanding, and give a theory of what it is to understand why proposition p is true. This view is based on the concept of probabilistic relevance matching, having one’s dispositions to believe p mirror the probabilistic relations that p has to all other matters. Based in probability, the view yields a clear relationship, and also distinction, between the concept of understanding and the concept of knowledge defined in terms of probabilistic tracking. With these tools we are able to see that gettierization avoidance has a value independent of the value of knowledge, viz. understanding, but that it is also in the nature of tracking-type knowledge to discourage gettierization quite specifically. The concept of understanding here captures several key features of this phenomenon, such as breadth, depth, and appreciation of connections, and allows us to see understanding as simulation.

What is it for the verdict of a criminal trial to be just? It is widely agreed that a Guilty verdict is just only if the defendant did the relevant deed, and only if his rights were not violated in the process of apprehending, charging, and convicting him. I argue that more is required: he must be found Guilty because he is guilty, and not solely for other reasons. The conviction must be based on the guilt. I argue that many rules of evidence and procedural rules designed to protect a defendant's rights also encourage fulfillment of this basing condition and that the condition helps to explain how an erroneous conviction involving no misconduct can nevertheless be a moral wrong. I argue that the condition also gives an explanation (among others) of why a naked statistic is insufficient for a just conviction.

In this study I investigate routes through which empirical conditions required for activities of knowing come to be relevant to questions of justification, relevant, that is, to questions about what can be concluded from evidence gathered. Thus it investigates concretely the reasoning at several sites where conditions external to the knower's mind become important to internal questions of justification. ;In Chapter 2 I analyze the reasoning associated with the Weak Anthropic Principle ---"what we observe may be restricted by the conditions necessary for our presence as observers." I show that this reasoning is not a straightforward application of the principle of total evidence, as has been claimed by John Earman, and hence is not a trivial instance of familiar rules of reasoning, as is widely believed. I begin the task of analyzing the general notion of a selection effect, and show that Copernicus argued for a Weak Anthropic selection effect in his suggestion that the earth moves. ;Chapter 3 gives a general account of transcendental arguments by identifying a distinctive piece of logical form which all such arguments share. This analysis shows that transcendental arguments need not have a priori premises, that Weak Anthropic reasoning is transcendental reasoning, and that transcendental arguments can generate as well as defuse skepticism. ;In Chapter 4 I identify reasoning about selection effects with reasoning about failure of provisoes , and investigate the role of this masoning in common and uncommon practices of discounting evidence. In the common case of a selection effect the grounds for believing there is a selection effect in evidence are independent of the theory under test. Cases where this fails are found in revolutionary science: Copernicus's hypothesis, the Marxist notion of false consciousness, and Newton's first law. I argue that self-insulation from falsification is found in some of our best scientific theories, and thus cannot by itself serve to disqualify a theory from scientificity. Further, such cases of selection effect expose a possible view of scientific revolutions according to which we can understand how disputes become inadjudicable without assuming theory-ladenness of observation

Physicist J. Richard Gott uses the Copernican principle that “we are not special” to make predictions about the future lifetime of the human race, based on how long the human race has been in existence so far. We show that the predictions which can be derived from Gott’s argument are less strong than one might be inclined to believe, that Gott’s argument illegitimately assumes that the human race will not last forever, that certain versions of Gott’s argument are incompatible with Bayesian conditionalization, and that Gott’s argument is self-refuting. *****Note: For Bradley Monton's up-to-date thoughts on Gott's argument, see his _Philosophical Quarterly_ paper co-authored with Brian Kierland, "How To Predict Future Duration from Present Age".*****

What is it for the verdict of a criminal trial to be just? It is widely agreed that a Guilty verdict is just only if the defendant did the relevant deed, and only if his rights were not violated in the process of apprehending, charging, and convicting him. I argue that more is required: he must be found Guilty because he is guilty, and not solely for other reasons. The conviction must be based on the guilt. I argue that many rules of evidence and procedural rules designed to protect a defendant's rights also encourage fulfillment of this basing condition and that the condition helps to explain how an erroneous conviction involving no misconduct can nevertheless be a moral wrong. I argue that the condition also gives an explanation (among others) of why a naked statistic is insufficient for a just conviction.

How confident does the history of science allow us to be about our current well-tested scientific theories, and why? The scientific realist thinks we are well within our rights to believe our best-tested theories, or some aspects of them, are approximately true.2 Ambitious arguments have been made to this effect, such as that over historical time our scientific theories are converging to the truth, that the retention of concepts and claims is evidence for this, and that there can be no other serious explanation of the success of science than that its theories are approximately true. There is appeal in each of these ideas, but making such strong claims has tended to be hazardous, leaving us open to charges that many typical episodes in the history of science just do not fit the model. (See, e.g., Laudan 1981.) Arguing for a realist attitude via general claims – properties ascribed to sets of theories, trends we see in progressions of theories, and claimed links between general properties like success and truth that apply or fail to apply to any theory regardless of its content – is like arguing for or via a theory of science, which brings with it the obligation to defend that theory. I think a realist attitude toward particular scientific theories for which we have evidence can be maintained rationally without such a theory, even in the face of the pessimistic induction over the history of science. The starting point at which questions arise as to what we have a right to believe about our theories is one where we have theories and evidence for them, and we are involved in the activity of apportioning our belief in each particular theory or hypothesis in accord with the strength of the particular evidence.3 The devil’s advocate sees our innocence and tries his best to sow seeds of doubt. If our starting point is as I say, though, the innocent believer in particular theories does not have to play offense and propose sweeping views about science in general, but only to respond to the skeptic’s challenges; the burden of initial argument is on the skeptic..

Epistemic injustice is injustice to a person qua knower. In one form of this phenomenon a speaker’s testimony is denied credence in a way that wrongs them. I argue that the received definition of this testimonial injustice relies too heavily on epistemic criteria that cannot explain why the moral concept of injustice should be invoked. I give an account of the nature of the wrong of epistemic injustice that has it depend not on the accuracy of judgments that are used or made in the process of deciding whether to listen to or trust a speaker, but on whether the basis of the decision about a speaker is their reliability or their identity, and the account explains why the latter is a moral wrong. A key difference between the two accounts is how they classify the use of true statistical generalizations connecting identity and reliability. The received view implies that this cannot be an injustice, while the view proposed here implies that it can. As such the new view appears to imply a conflict between moral and epistemic obligations: it is morally wrong to use true statistical generalizations in certain contexts, yet they are part of our evidence, and we are epistemically obligated to take all of our evidence into account. I reconcile these two thoughts without adopting the currently popular view that a belief’s being morally wrong makes it epistemically unjustified, and I argue that following the principle of total evidence encourages epistemic justice rather than thwarting it.

Many who think that naked statistical evidence alone is inadequate for a trial verdict think that use of probability is the problem, and something other than probability – knowledge, full belief, causal relations – is the solution. I argue that the issue of whether naked statistical evidence is weak can be formulated within the probabilistic idiom, as the question whether likelihoods or only posterior probabilities should be taken into account in our judgment of a case. This question also identifies a major difference between the Process Reliabilist and Probabilistic Tracking views of knowledge and other concepts. Though both are externalist, and probabilistic, epistemic theories, Tracking does and Process Reliabilism does not put conditions on likelihoods. So Tracking implies that a naked statistic is not adequate evidence about an individual, and does not yield knowledge, whereas the Reliabilist thinks it gives justified belief and knowledge. Not only does the Tracking view imply that naked statistical evidence is insufficient for a verdict, but it gives us resources to explain why, in terms of risk and the special conditions of a trial.

Why should we make our beliefs consistent or, more generally, probabilistically coherent? That it will prevent sure losses in betting and that it will maximize one’s chances of having accurate beliefs are popular answers. However, these justifications are self-centered, focused on the consequences of our coherence for ourselves. I argue that incoherence has consequences for others because it is liable to mislead others, to false beliefs about one’s beliefs and false expectations about one’s behavior. I argue that the moral obligation of truthfulness thus constrains us to either conform to the logic our audience assumes we use, educate them in a new logic, or give notice that one will do neither. This does not show that probabilistic coherence is uniquely suited to making truthful communication possible, but I argue that classical probabilistic coherence is superior to other logics for maximizing efficiency in communication.

Health anxiety is, among other things, a response to a universal epistemological problem about whether changes in one’s body indicate serious illness, a problem that grows more challenging to the individual with age and with every advance in medical science, detection, and treatment. There is growing evidence that dysfunctional metacognitive beliefs – beliefs about thinking – are the driving factor, with dysfunctional substantive beliefs about the probability of illness a side‐effect, and that Metacognitive Therapy (MCT) is more effective than Cognitive Behavioral Therapy (CBT). However, hypochondria is distinct from other forms of anxiety, I argue, in ways that make some reality‐checking techniques of CBT and MCT of limited usefulness. I propose a Re‐Calibration Technique (RCT) that complements these therapies by focusing on a metacognitive belief that has not been studied: the patient’s presumption of his own personal reliability in judging symptoms, an assumption exposed every time he disagrees with a doctor. I propose a technique whereby a patient keeps a long‐term register of every episode of alarm about symptoms and its resolution, possibly years later. When healthcare‐seeking impulses arise the patient then uses his own track record to re‐calibrate his confidence that medical attention is needed. The new technique allows one to improve self‐judgment about whether one has an illness or not by improving self‐knowledge of one’s own reliability.

Self-knowledge has always played a role in healthcare since a person needs to be able to accurately assess her body or behaviour in order to determine whether to seek medical help. But more recently it has come to play a larger role, as healthcare has moved from a more paternalistic model to one where patients are expected to take charge of their health; as we realise that early detection, and hence self-examination, can play a crucial role in outcomes; as medical science improves and makes more terminal illnesses into chronic conditions requiring self-management; as genetic testing makes it possible to have more information about our futures; and with the advent of personal electronic devices that make it easy for a person to gather accurate real-time information about her body. It can be hard to get good information about oneself, and even harder to know what to do it. Sometimes self-knowledge is needed for a good outcome, but sometimes it is useless, or worse. For instance, breast self-examination can lead to over-treatment, learning that one has a predisposing gene can create a detrimental illusion of knowing more about the future than one does, and data about one’s vital signs can be meaningless if taken out of a context of interpretation. This collection explores how these and other issues play out in a variety of medical specialities.

In the aftermath of Gettier’s examples, knowledge came to be thought of as what you would have if in addition to a true belief and your favorite epistemic goody, such as justifiedness, you also were ungettiered, and the theory of knowledge was frequently equated, especially by its detractors, with the project of pinning down that extra bit. It would follow that knowledge contributes something distinctive that makes it indispensable in our pantheon of epistemic concepts only if avoiding gettierization has a value that can be explained without presupposing the value of knowledge. Tracking-type knowledge has a value that no other logically possible conditions on true belief does. As an Evolutionarily Stable Strategy it preserves appropriate belief states through time and changing circumstances. If we characterize gettierization through the concept of relevance matching, then we see that avoiding gettierization has a value independent of that of knowledge, namely, understanding, and that it is unnecessary to add a clause to the tracking conditions to make them suppress gettierization directly, though fallibly. The bright line of value is between gettierization avoidance and understanding on the one hand and knowledge on the other, and so should be the bright line defining concepts. The concept of relevance matching is key to a definition of what it is to understand why p is true, as opposed merely to knowing that p is true. Perfect tracking implies perfect relevance matching, so knowledge and understanding are intimately connected but understanding also requires that one own states that accomplish the relevance matching rather than achieving it vicariously. The theory of understanding based on relevance matching implies that understanding requires appreciation of not only p but its connections to other matters, and explains how it is possible to know that p is true without understanding why. The view implies that understanding is literally simulation, and is suggestive about understanding other minds.

One of the most common criticisms one hears of the idea of granting a legitimate role for social values in theory choice in science is that it just doesn’t make sense to regard social preferences as relevant to the truth or to the way things are. “What is at issue,” wrote Susan Haack, is “whether it is possible to derive an ‘is’ from an ‘ought.’ ” One can see that this is not possible, she concludes, “as soon as one expresses it plainly: that propositions about what states of affairs are desirable or deplorable could be evidence that things are, or are not, so” (Haack 1993a, 35, emphasis in original). The purpose of this chapter is not to determine whether this widespread view is correct, but rather to show that even if we grant it (which I do), we may still consistently believe that social values have a legitimate role in theory choice in science. I will defend this conclusion by outlining a view about social values and theory choice that is available to a Constructive Empiricist anti-realist, but not to a realist.

This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of dispute over the epistemic superiority thesis have assumed. The superiority depends on features of the question and on a property of natural kinds that has been mistaken for material similarity. Seeing this requires holding other things equal in the comparison of the two methods, thereby exposing that, under the conditions that will be specified, the simulation is necessarily epistemically one step behind the corresponding experiment. Practical constraints like feasibility and morality mean that scientists do not often face an other-things- equal comparison when they choose between experiment and simulation. Nevertheless, I argue, awareness of this superiority and of the general distinction between experiment and simulation is important for maintaining motivation to seek answers to new questions.

Abstract: Knowledge requires more than mere true belief, and we also tend to think it is more valuable. I explain the added value that knowledge contributes if its extra ingredient beyond true belief is tracking . I show that the tracking conditions are the unique conditions on knowledge that achieve for those who fulfill them a strict Nash Equilibrium and an Evolutionarily Stable Strategy in what I call the True Belief Game. The added value of these properties, intuitively, includes preparedness and an expectation of survival advantage. On this view knowledge is valuable not because knowledge persists but because it makes the bearer more likely to maintain an appropriate belief state—possibly nonbelief—through time and changing circumstances. When Socrates concluded that knowledge of the road to Larissa was no more valuable than true belief for the purpose of getting to Larissa, he did not take into account that one might want to be prepared for a possible meeting with a misleading sophist along the way, or for the possibility of road work.

Sherrilyn Roush defends a new theory of knowledge and evidence, based on the idea of "tracking" the truth, as the best approach to a wide range of questions about knowledge-related phenomena. The theory explains, for example, why scepticism is frustrating, why knowledge is power, and why better evidence makes you more likely to have knowledge. Tracking Truth provides a unification of the concepts of knowledge and evidence, and argues against traditional epistemological realist and anti-realist positions about scientific theories and for a piecemeal approach based on a criterion of evidence, a position Roush calls "real anti-realism." Epistemologists and philosophers of science will recognize this as a significant original contribution

Relatively few philosophers of science today could do all of what Nicholas Maxwell does without hesitating: treat theoretical physics as indicative of all science because it is deemed fundamental, observe and expect science to exhibit a cumulative history of more and more unified knowledge, claim to solve the problem of induction, and insist that philosophy, particularly metaphysics, is crucially relevant to ongoing progress in science. Maxwell is distinctly out of fashion—this is no dappled world—but in hewing to a line he has been developing for decades he presents several intriguing and intertwined proposals for understanding and continuing the progress of physics over the last three and a half centuries toward a single, true, theory of everything.

I develop a general framework with a rationality constraint that shows how coherently to represent and deal with second-order information about one's own judgmental reliability. It is a rejection of and generalization away from the typical Bayesian requirements of unconditional judgmental self-respect and perfect knowledge of one's own beliefs, and is defended by appeal to the Principal Principle. This yields consequences about maintaining unity of the self, about symmetries and asymmetries between the first- and third-person, and a principled way of knowing when to stop second-guessing oneself. Peer disagreement is treated as a special case where one doubts oneself because of news that an intellectual equal disagrees. This framework, and variants of it, imply that the typically stated belief that an equally reliably peer disagrees is incoherent, and thus that pure rationality constraints without further substantive information cannot give an answer as to what to do. The framework also shows that treating both ourselves and others as thermometers in the disagreement situation does not imply the Equal Weight view

Deduction is important to scientific inquiry because it can extend knowledge efficiently, bypassing the need to investigate everything directly. The existence of closure failure—where one knows the premises and that the premises imply the conclusion but nevertheless does not know the conclusion—is a problem because it threatens this usage. It means that we cannot trust deduction for gaining new knowledge unless we can identify such cases ahead of time so as to avoid them. For philosophically engineered examples we have “inner alarm bells” to detect closure failure, but in scientific investigation we would want to use deduction for extension of our knowledge to matters we don’t already know that we couldn’t know. Through a quantitative treatment of how fast probabilistic sensitivity is lost over steps of deduction, I identify a condition that guarantees that the growth of potential error will be gradual; thus, dramatic closure failure is avoided. Whether the condition is fulfilled is often obvious, but sometimes it requires substantive investigation. I illustrate that not only safe deduction but the discovery of dramatic closure failures can lead to scientific advances.

On analogy with testimony, I define a notion of a scientific theory’s lacking or having candor, in a testing situation, according to whether the theory under test is probabilistically relevant to the processes in the test procedures, and thereby to the reliability of test outcomes. I argue that this property identifies what is distinctive about those theories that Karl Popper denounced as exhibiting “reinforced dogmatism” through their self-protective behavior (e.g., psychoanalysis, Hegelianism, Marxism). I explore whether lack of candor interferes with the testing of theories, and conclude that (1) our default attitude toward theories that lack candor in a given test should be suspicion, but (2) the circumstance that a theory lacks candor in a testing situation does not preclude obtaining independent evidence for the auxiliary assumptions to which the theory is probabilistically relevant, and thereby eliminating the problem that lack of candor creates. Thus, Popper was right to think that lack of candor is a bad thing, but wrong to conclude that candor is a criterion of the scientificity of a theory. Seeing this requires recognition of some differences between intuitive relevance and probabilistic relevance, and proper appreciation of the notion of screening off and of the fact that probabilistic relevance is not transitive.