I critically examine confirmational holism as it pertains to the indispensability arguments for mathematical Platonism. I employ a distinction between pure and applied mathematics that grows out of the often overlooked symbiotic relationship between mathematics and science. I argue that this distinction undercuts the notion that mathematical theories fall under the holistic scope of the confirmation of our scientific theories.Keywords: Confirmational holism; Indispensability argument; Mathematics; Application; Science.

Robustness may increase the degree to which the robust result is indirectly confirmed if it is shown to depend on confirmed rather than disconfirmed assumptions. Although increasing the weight with which existing evidence indirectly confirms it in such a case, robustness may also be irrelevant for confirmation, or may even disconfirm. Whether or not it confirms depends on the available data and on what other results have already been established.

Nelson Goodman suggests that a generalization of the form “all A’s are B” is confirmable by an observed instance only if the generalization is law-like. Jackson and Pargetter deny this and give examples of how accidental generalizations can be confirmed. A possible response from Goodman appears to make these accidental generalizations look law-like, but I show it’s defective. And Jackson and Pargetter's substitute nomological condition fares no better than Goodman’s. Because of the multiplicity of possible background assumptions, I doubt that (...) there is a single “nomological condition” that each and every act of confirmation must obey. (shrink)

An experiment is reported which tests for positive confirmation bias in a setting in which individuals choose what information to buy, prior to making a decision. The design – an adaptation of Wason's selection task – reveals the use that subjects make of information after buying it. Strong evidence of positive confirmation bias, in both information acquisition and information use, is found; and this bias is found to be robust to experience. It is suggested that the bias results (...) from a pattern of reasoning which, although producing sub-optimal decisions, is internally coherent and which is self-reinforcing. (shrink)

Van Fraassen argues that explanatory power cannot be a conformational virtue. In this paper I will show that informational features of scientific theories can be positively relevant to their levels of conformation. Thus, in the cases where the explanatory power of a theory is tied to an informational feature of the theory, it can still be the case that the explanatory power of the theory is positively relevant to its level of confirmation.

Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their (...) model as a general approach to analogical inference and argue that these problems can be avoided by supplementing Bayesian update with Jeffrey conditionalization. (shrink)

So far no known measure of confirmation of a hypothesis by evidence has satisfied a minimal requirement concerning thresholds of acceptance. In contrast, Shogenji’s new measure of justification (Shogenji, Synthese, this number 2009) does the trick. As we show, it is ordinally equivalent to the most general measure which satisfies this requirement. We further demonstrate that this general measure resolves the problem of the irrelevant conjunction. Finally, we spell out some implications of the general measure for the Conjunction Effect; (...) in particular we give an example in which the effect occurs in a larger domain, according to Shogenji justification, than Carnap’s measure of confirmation would have led one to expect. (shrink)

This paper proposes a framework for representing in Bayesian terms the idea that analogical arguments of various degrees of strength may provide inductive support to yet untested scientific hypotheses. On this account, contextual information plays a crucial role in determining whether, and to what extent, a given similarity or dissimilarity between source and target may confirm an empirical hypothesis over a rival one. In addition to showing confirmation by analogy compatible with the adoption of a Bayesian standpoint, the proposal (...) outlined in this paper reveals a close agreement between the fulfillment of Hesse’s (Models and analogies in science, University of Notre Dame Press, 1963) criteria for analogical arguments capable of inductive support and the attribution of confirmatory power by the lights of Bayesian confirmation theory. In this sense, the Bayesian representation not only enriches a framework, Hesse’s, of enduring relevance for understanding scientific activity, but may offer something akin to a proof of concept of it. (shrink)

The tendency to test outcomes that are predicted by our current theory (the confirmation bias) is one of the best-known biases of human decision making. We prove that the confirmation bias is an optimal strategy for testing hypotheses when those hypotheses are deterministic, each making a single prediction about the next event in a sequence. Our proof applies for two normative standards commonly used for evaluating hypothesis testing: maximizing expected information gain and maximizing the probability of falsifying the (...) current hypothesis. This analysis rests on two assumptions: (a) that people predict the next event in a sequence in a way that is consistent with Bayesian inference; and (b) when testing hypotheses, people test the hypothesis to which they assign highest posterior probability. We present four behavioral experiments that support these assumptions, showing that a simple Bayesian model can capture people's predictions about numerical sequences (Experiments 1 and 2), and that we can alter the hypotheses that people choose to test by manipulating the prior probability of those hypotheses (Experiments 3 and 4). (shrink)

Philosophers of science have offered various accounts of climate model evaluation which have largely centered on model-fit assessment. However, despite the wide-spread prevalence of process-based evaluation in climate science practice, this sort of model evaluation has been undertheorized by philosophers of science. In this paper, I aim to expand this narrow philosophical view of climate model evaluation by providing a philosophical account of process evaluation that is rooted in a close examination of scientific practice. I propose dynamical adequacy as a (...) metric by which scientists test and evaluate models that represent and produce key regional climate processes and features. I argue that process-based evaluation confirms the adequacy of a regional climate model for simulating and predicting future changes of a specific regional climate feature. I offer a case study of how, in practice, scientists establish the reliability of model projections by assessing the dynamical adequacy of such models. I also show how process-based evaluation mitigates some well-known shortcomings of model-fit assessment and supports the adequacy and reliability of climate model projections against philosophical objections, like confirmational holism. Such adequacy is especially important for decision makers who need reliable regional model projections to guide their climate change mitigation and adaptation policies. (shrink)

Glymour’s theory of bootstrap confirmation is a purely qualitative account of confirmation; it allows us to say that the evidence confirms a given theory, but not that it confirms the theory to a certain degree. The present paper extends Glymour’s theory to a quantitative account and investigates the resulting theory in some detail. It also considers the question how bootstrap confirmation relates to justification.

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods (...) or priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (shrink)

There are some candidates that have been thought to measure the degree to which evidence incrementally confirms a hypothesis. This paper provides an argument for one candidate—the log-likelihood ratio measure. For this purpose, I will suggest a plausible requirement that I call the Requirement of Collaboration. And then, it will be shown that, of various candidates, only the log-likelihood ratio measure \(l\) satisfies this requirement. Using this result, Jeffrey conditionalization will be reformulated so as to disclose explicitly what determines new (...) credences after experience. (shrink)

Two types of idealization in theory construction are distinguished, and the distinction is used to give a critique of Ron Laymon's account of confirming idealized theories and his argument for scientific realism.

The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of _confirmation_ relations, meant in terms of contemporary Bayesian confirmation theory. Our main (...) formal result is a confirmation-theoretic account of the conjunction fallacy, which is proven _robust_ (i.e., not depending on various alternative ways of measuring degrees of confirmation). The proposed analysis is shown distinct from contentions that the conjunction effect is in fact not a fallacy, and is compared with major competing explanations of the phenomenon, including earlier references to a confirmation-theoretic account. (shrink)

The Diagnosis Confirmation Model includes a dual-pricing mechanism designed to support value-based pricing of novel antibiotics while improving the alignment of financial incentives with their optimal use in patients at high risk of drug-resistant infections. DCM is a market-based model and complementary to delinked models. Policymakers interested in stimulating antibiotic innovation could consider tailoring the DCM to their reimbursement systems and incorporating it into the suite of incentives to improve the economics of antibiotics.

The Quine/Putnam indispensability approach to the confirmation of mathematical theories in recent times has been the subject of significant criticism. In this paper I explore an alternative to the Quine/Putnam indispensability approach. I begin with a van Fraassen-like distinction between accepting the adequacy of a mathematical theory and believing in the truth of a mathematical theory. Finally, I consider the problem of moving from the adequacy of a mathematical theory to its truth. I argue that the prospects for justifying (...) this move are qualitatively worse in mathematics than they are in science. (shrink)

According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are correlated under Pr. Surprisingly, this leads to a plethora of non-equivalent quantitative measures of the degree to which E confirms H (under Pr). In fact, many non-equivalent Bayesian measures of the degree to which E confirms (...) (or supports) H have been proposed and defended in the literature on inductive logic. I provide a thorough historical survey of the various proposals, and a detailed discussion of the philosophical ramifications of the differences between them. I argue that the set of candidate measures can be narrowed drastically by just a few intuitive and simple desiderata. In the end, I provide some novel and compelling reasons to think that the correct measure of degree of evidential support (within a Bayesian framework) is the (log) likelihood ratio. The central analyses of this research have had some useful and interesting byproducts, including: (i ) a new Bayesian account of (confirmationally) independent evidence, which has applications to several important problems in con- firmation theory, including the problem of the (confirmational) value of evidential diversity, and (ii ) novel resolutions of several problems in Bayesian confirmation theory, motivated by the use of the (log) likelihood ratio measure, including a reply to the Popper-Miller critique of probabilistic induction, and a new analysis and resolution of the problem of irrelevant conjunction (a.k.a., the tacking problem). (shrink)

The purpose of the present note is to advertise an interesting conjecture concerning a well-known translation in modal logic, by confirming a (highly restricted) special case of the conjecture.

Darren Bradley has recently appealed to observation selection effects to argue that conditionalization presents no special problem for Everettian quantum mechanics, and to defend the ‘halfer’ answer to the puzzle of Sleeping Beauty. I assess Bradley’s arguments and conclude that while he is right about confirmation in Everettian quantum mechanics, he is wrong about Sleeping Beauty. This result is doubly good news for Everettians: they can endorse Bayesian confirmation theory without qualification, but they are not thereby compelled to (...) adopt the unpopular ‘halfer’ answer in Sleeping Beauty. These considerations suggest that objective chance is playing an important and under-appreciated role in Sleeping Beauty. (shrink)

Two declarative sentences are synonymous if, and only if, the statements they can be used to make are. given certain assumptions about the truth or falsity of other statements, confirmed or disconfirmed to the same degree by the same evidence. This criterion of synonymy is Quinean in that it treats confirmation holistically. But unlike Quine's criterion of synonymy, it conforms to and explains our intuitions of sentence synonymy.

Does confirmation holism imply meaning holism? A plausible and novel argument, all of whose premises enjoy significant support among contemporary philosophers, links the two theses. This article presents this argument and diagnoses it with a weakness. The weakness illustrates a general difficulty with drawing morals for the nature of ordinary thought and language from claims about the nature of science. The diagnosis is instructive: It suggests more fruitful relations between theories of scientific theory confirmation and semantic theories of (...) our everyday thoughts and statements. (shrink)

It is well known that the probabilistic relation of confirmation is not transitive in that even if E confirms H1 and H1 confirms H2, E may not confirm H2. In this paper we distinguish four senses of confirmation and examine additional conditions under which confirmation in different senses becomes transitive. We conduct this examination both in the general case where H1 confirms H2 and in the special case where H1 also logically entails H2. Based on these analyses, (...) we argue that the Screening-Off Condition is the most important condition for transitivity in confirmation because of its generality and ease of application. We illustrate our point with the example of Moore’s “proof” of the existence of a material world, where H1 logically entails H2, the Screening-Off Condition holds, and confirmation in all four senses turns out to be transitive. (shrink)

The extra value of novel confirmation over accommodation is explained based on an analysis of the underdetermination of scientific theory building. Novel confirmation can provide information on the number of possible scientific alternatives to a predictively successful theory. This information, in turn, can raise the probability that the given theory is true or will be empirically viable in the future.

Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation. In this article, we present a Bayesian analysis of how GNS impacts on confirmation. We formalize the relation between the reducing and the reduced theory before and after the reduction using Bayesian networks, and thereby show that, post-reduction, the two theories are confirmatory of each other. (...) We then ask when a purported reduction should be accepted on epistemic grounds. To do so, we compare the prior and posterior probabilities of the conjunction of both theories before and after the reduction and ask how well each is confirmed by the available evidence. (shrink)

This paper aims to show how Whewell's notions of consilience and unification-explicated in more modern probabilistic terms provide a satisfying treatment of cases of scientific discovery Which require the postulatioin component causes to explain complex events. The results of this analysis support the received view that the increased unification and generality of theories leads to greater testability, and confirmation if the observations are favorable. This solves a puzzle raised by Cartwright in How the Laws of Physics Lie about the (...) nature of explanation by the composition of causes. (shrink)

The purpose of this paper is to make a simple observation regarding the Johnson -Carnap continuum of inductive methods. From the outset, a common criticism of this continuum was its failure to permit the confirmation of universal generalizations: that is, if an event has unfailingly occurred in the past, the failure of the continuum to give some weight to the possibility that the event will continue to occur without fail in the future. The Johnson -Carnap continuum is the mathematical (...) consequence of an axiom termed Johnson 's sufficientness postulate, the thesis of this paper is that, properly viewed, the failure of the Johnson -Carnap continuum to confirm universal generalizations is not a deep fact, but rather an immediate consequence of the sufficientness postulate; and that if this postulate is modified in the minimal manner necessary to eliminate such an entailment, then the result is a new continuum that differs from the old one in precisely one respect: it enjoys the desideratum of confirming universal generalizations. (shrink)

Existing accounts of hypothetico-deductive confirmation are able to circumvent the classical objections, but the confirmation of conjunctions of hypotheses brings them into trouble. Therefore this paper develops a new, falsificationist account of qualitative confirmation by means of Ken Gemes ' theory of content parts. The new approach combines the hypothetico-deductive view with falsificationist and instance confirmation principles. It is considerably simpler than the previous suggestions and gives a better treatment of conjunctive hypotheses while solving the tacking (...) problems equally well. (shrink)

In this paper I distinguish various ways in which empirical claims about evolutionary and ecological models can be supported by data. I describe three basic factors bearing on confirmation of empirical claims: fit of the model to data; independent testing of various aspects of the model, and variety of evident. A brief description of the kinds of confirmation is followed by examples of each kind, drawn from a range of evolutionary and ecological theories. I conclude that the greater (...) complexity and precision of my approach, as compared to, for instance, a Popperian approach, can facilitate detailed analysis and comparison of empirical claims. (shrink)

Confirmation theory is intended to codify the evidential bearing of observations on hypotheses, characterizing relations of inductive “support” and “counter­support” in full generality. The central task is to understand what it means to say that datum E confirms or supports a hypothesis H when E does not logically entail H.

Darren Bradley has recently appealed to observation selection effects to argue that conditionalization presents no special problem for Everettian quantum mechanics, and to defend the ‘halfer’ answer to the puzzle of Sleeping Beauty. I assess Bradley’s arguments and conclude that while he is right about confirmation in Everettian quantum mechanics, he is wrong about Sleeping Beauty. This result is doubly good news for Everettians: they can endorse Bayesian confirmation theory without qualification, but they are not thereby compelled to (...) adopt the unpopular ‘halfer’ answer in Sleeping Beauty. These considerations suggest that objective chance is playing an important and under-appreciated role in Sleeping Beauty. 1 Introduction2 Confirmation in Everettian Quantum Mechanics3 Sleeping Beauty4 The Selection Model5 Bradley’s Argument6 The Right Route to ⅓7 The Breakdown of the Analogy8 Alternative Diagnoses9 God’s Gambling Game10 Non-chancy Sleeping Beauty Cases11 Conclusion. (shrink)

Applies the models to the confirmation of scientific hypotheses by means of partially reliable test instruments. Shows that the variety-of-evidence thesis is false under certain plausible interpretations and assesses the Duhem–Quine thesis for positively relevant versus independent hypotheses and auxiliaries.

has proposed an interesting and novel Bayesian analysis of the Quine-Duhem (Q–D) problem (i.e., the problem of auxiliary hypotheses). Strevens's analysis involves the use of a simplifying idealization concerning the original Q–D problem. We will show that this idealization is far stronger than it might appear. Indeed, we argue that Strevens's idealization oversimplifies the Q–D problem, and we propose a diagnosis of the source(s) of the oversimplification. Some background on Quine–Duhem Strevens's simplifying idealization Indications that (I) oversimplifies Q–D Strevens's argument (...) for the legitimacy of (I). (shrink)

There is a plethora of confirmation measures in the literature. Zalabardo considers four such measures: PD, PR, LD, and LR. He argues for LR and against each of PD, PR, and LD. First, he argues that PR is the better of the two probability measures. Next, he argues that LR is the better of the two likelihood measures. Finally, he argues that LR is superior to PR. I set aside LD and focus on the trio of PD, PR, and (...) LR. The question I address is whether Zalabardo succeeds in showing that LR is superior to each of PD and PR. I argue that the answer is negative. I also argue, though, that measures such as PD and PR, on one hand, and measures such as LR, on the other hand, are naturally understood as explications of distinct senses of confirmation. (shrink)

ABSTRACT This article aims to achieve two things: to identify the conditions for transitivity in probabilistic support in various settings, and to uncover the components and structure of the mediated probabilistic relation. It is shown that when the probabilistic relation between the two propositions, x and z, is mediated by multiple layers of partitions of propositions, the impact x has on z consists of the purely indirect impact, the purely bypass impact, and the mixed impact. It is also shown that (...) although mediated confirmation as a whole is not transitive, the indirect part of mediated confirmation is transitive. _1_ Introduction _2_ The Structure of the Mediated Probabilistic Relation _3_ Transitivity and Anti-transitivity _4_ Bypass Disconfirmation _5_ Horizontal Generalization _6_ Coarse Screens _7_ Vertical Generalization _8_ Conclusion Appendix. (shrink)

The general objective of nursing supervision is to support the development of the super-visee’s job identity, competence, skills and ethics. This can be achieved through the stages of the supervision process. The aim of this article is to describe and discuss such a nursing supervision model, as well as the supervisor’s competence and moral responsibility, by analysing the interpretation of nursing supervision. Three main concepts are described: confirmation, meaning and self-awareness. The findings suggest that these concepts need to be (...) established in the nursing supervision process by the supervisor, who is morally responsible for applying the process and for establishing a relationship with the supervisees. (shrink)

In this chapter probability and confirmation theory are used to investigate the problem of evil, concentrating on whether a theist should consider our ignorance of a good reason for God to permit evil to support a non-religious alternative over a typical theist's beliefs. It is argued that according to Likelihoodism, our ignorance of a good reason does not favor a competing hypothesis over the religious view that there is an incomprehensible good reason for God to permit evil. Bayesian accounts (...) of comparative confirmation, which are alternatives to Likelihoodism, have the same result. Furthermore, according to both Likelihoodism and Bayesian accounts of contrastive confirmation, our ignorance of a good reason for God to permit evil may actually support typical religious beliefs over the alternative hypotheses. (shrink)

A recent development in the philosophy of religion has been the attempt to justify belief in God using Bayesian confirmation theory. My dissertation critically discusses two prominent spokesmen for this approach--Richard Swinburne and J. L. Mackie. Using probabilistic confirmation theory, these philosophers come to wildly divergent conclusions with respect to the hypothesis of theism; Swinburne contends that the evidence raises the overall probability of the hypothesis of theism, whereas Mackie argues that the evidence disconfirms the existence of God. (...) After a careful analysis of the individual authors, this dissertation critically examines the assumptions of the project. The authors consider arguments for the existence of God separately--the cosmological argument, the argument from design, apparent miracles, the problem of evil, and arguments from religious experience--and then conjoin them to assess the cumulative effect of the arguments. The assumptions are that the probability calculus may be interpreted for a successful inductive argument for or against the existence of God, that inference to best explanation is applicable to the justification of religious belief, that the justification of belief in God is analogous to the justification of a scientific theory, and that a classical foundationalist conception of rationality is correct. It is the contention of this dissertation that all of these assumptions are incorrect. All of the major interpretations of the probability calculus are examined and it is argued that there are either no interpretations for the probability assignments or no interpretations which will advance an argument for or against the existence of God. It is also argued that the usual methods for interpreting the explanatory power of theism will not determine any non-zero probabilities; however, density measuring will provide a non-zero interpretation. In the final chapter it is argued that a subjective Bayesian conception of rationality is neither a necessary nor a sufficient condition of rationality and that classical foundationalism is self-referentially inconsistent. An alternative approach to the rationality of religious belief is offered that proceeds along Reidian and Plantingan lines, belief in God is properly basic. (shrink)

Quine and Putnam argued for mathematical realism on the basis of the indispensability of mathematics to science. They claimed that the mathematics that is used in physical theories is confirmed along with those theories and that scientific realism entails mathematical realism. I argue here that current theories of confirmation suggest that mathematics does not receive empirical support simply in virtue of being a part of well confirmed scientific theories and that the reasons for adopting a realist view of scientific (...) theories do not support realism about mathematical entities, despite the use of mathematics in formulating scientific theory. (shrink)

Confirmation and falsification are different strategies for testing theories and characterizing the outcomes of those tests. Roughly speaking, confirmation is the act of using evidence or reason to verify or certify that a statement is true, definite, or approximately true, whereas falsification is the act of classifying a statement as false in the light of observation reports. After expounding the intellectual history behind confirmation and falsificationism, reaching back to Plato and Aristotle, I survey some of the main (...) controversial issues and arguments that pertain to the choice between these strategies: the Raven Paradox, the Duhem/Quine problem and the Grue Paradox. Finally, I outline an evolutionary criticism of inductive Bayesian approaches based on my assumption of doxastic involuntarism. (shrink)

This brief annotated bibliography is intended to help students get started with their research. It is not a substitute for personal investigation of the literature, and it is not a comprehensive bibliography on the subject. For those just beginning to study probabilistic confirmation theory and Bayesian reasoning, I suggest the starred items as good places to start your reading.

Bayesian confirmation theory is rife with confirmation measures. Zalabardo focuses on the probability difference measure, the probability ratio measure, the likelihood difference measure, and the likelihood ratio measure. He argues that the likelihood ratio measure is adequate, but each of the other three measures is not. He argues for this by setting out three adequacy conditions on confirmation measures and arguing in effect that all of them are met by the likelihood ratio measure but not by any (...) of the other three measures. Glass and McCartney, hereafter “G&M,” accept the conclusion of Zalabardo’s argument along with each of the premises in it. They nonetheless try to improve on Zalabardo’s argument by replacing his third adequacy condition with a weaker condition. They do this because of a worry to the effect that Zalabardo’s third adequacy condition runs counter to the idea behind his first adequacy condition. G&M have in mind confirmation in the sense of increase in probability: the degree to which E confirms H is a matter of the degree to which E increases H’s probability. I call this sense of confirmation “IP.” I set out four ways of precisifying IP. I call them “IP1,” “IP2,” “IP3,” and “IP4.” Each of them is based on the assumption that the degree to which E increases H’s probability is a matter of the distance between p and a certain other probability involving H. I then evaluate G&M’s argument in light of them. (shrink)

Having a confirmation bias sometimes leads us to hold inaccurate beliefs. So, the puzzle goes: why do we have it? According to the influential argumentative theory of reasoning, confirmation bias emerges because the primary function of reason is not to form accurate beliefs, but to convince others that we’re right. A crucial prediction of the theory, then, is that confirmation bias should be found only in the reasoning domain. In this article, we argue that there is evidence (...) that confirmation bias does exist outside the reasoning domain. This undermines the main evidential basis for the argumentative theory of reasoning. In presenting the relevant evidence, we explore why having such confirmation bias may not be maladaptive. (shrink)

Neurolaw is the emerging research field and practice of applying neuroscientific knowledge to legal standards and proceedings. This intersection of neuroscience and law has put up some serious claims, the most significant of which is the overall transformation of the legal system as we know it. The claim has met with strong opposition from scholars of law, such as Michael Pardo and Dennis Patterson (2011), who argue that neurolaw (and neuroscience more generally) is conceptually wrong and thus perceive most of (...) it as “nonsense” (Patterson, 2003). I expose a flaw in Pardo and Patterson’s arguments by means of confirmation theory. My main point is that Pardo and Patterson use implicit hypothetico-deductivism in their attack on neurolaw, and that we have good reasons to doubt the employment of such a model, because it faces serious theoretical problems. I then demonstrate how the alleged problems associated with neurolaw disappear if we use a quantitative probabilistic account of confirmation. I also explain why it provides a better account for the way the legal system actually works. (shrink)