Recently, the practice of deciding legal cases on purely statistical evidence has been widely criticised. Many feel uncomfortable with finding someone guilty on the basis of bare probabilities, even though the chance of error might be stupendously small. This is an important issue: with the rise of DNA profiling, courts are increasingly faced with purely statistical evidence. A prominent line of argument—endorsed by Blome-Tillmann 2017; Smith 2018; and Littlejohn 2018—rejects the use of such evidence by appealing to epistemic norms (...) that apply to individual inquirers. My aim in this paper is to rehabilitate purely statistical evidence by arguing that, given the broader aims of legal systems, there are scenarios in which relying on such evidence is appropriate. Along the way I explain why popular arguments appealing to individual epistemic norms to reject legal reliance on bare statistics are unconvincing, by showing that courts and individuals face different epistemic predicaments (in short, individuals can hedge when confronted with statistical evidence, whilst legal tribunals cannot). I also correct some misconceptions about legal practice that have found their way into the recent literature. (shrink)

Martin Smith has recently proposed, in this journal, a novel and intriguing approach to puzzles and paradoxes in evidence law arising from the evidential standard of the Preponderance of the Evidence. According to Smith, the relation of normic support provides us with an elegant solution to those puzzles. In this paper I develop a counterexample to Smith’s approach and argue that normic support can neither account for our reluctance to base affirmative verdicts on bare statistical evidence nor resolve the (...) pertinent paradoxes. Normic support is, as a consequence, not a successful epistemic anti-luck condition. (shrink)

The paper takes a closer look at the role of knowledge and evidence in legal theory. In particular, the paper examines a puzzle arising from the evidential standard Preponderance of the Evidence and its application in civil procedure. Legal scholars have argued since at least the 1940s that the rule of the Preponderance of the Evidence gives rise to a puzzle concerning the role of statistical evidence in judicial proceedings, sometimes referred to as the Problem of Bare Statistical Evidence. (...) While this puzzle has led to the development of a multitude of accounts and approaches in the legal literature, I argue here that the problem can be resolved fairly straightforwardly within a knowledge-first framework. (shrink)

Recent attempts to resolve the Paradox of the Gatecrasher rest on a now familiar distinction between individual and bare statistical evidence. This paper investigates two such approaches, the causal approach to individual evidence and a recently influential (and award-winning) modal account that explicates individual evidence in terms of Nozick's notion of sensitivity. This paper offers counterexamples to both approaches, explicates a problem concerning necessary truths for the sensitivity account, and argues that either view is implausibly committed to the impossibility (...) of no-fault wrongful convictions. The paper finally concludes that the distinction between individual and bare statistical evidence cannot be maintained in terms of causation or sensitivity. We have to look elsewhere for a solution of the Paradox of the Gatecrasher. (shrink)

A question, long discussed by legal scholars, has recently provoked a considerable amount of philosophical attention: ‘Is it ever appropriate to base a legal verdict on statistical evidence alone?’ Many philosophers who have considered this question reject legal reliance on bare statistics, even when the odds of error are extremely low. This paper develops a puzzle for the dominant theories concerning why we should eschew bare statistics. Namely, there seem to be compelling scenarios in which there (...) are multiple sources of incriminating statistical evidence. As we conjoin together different types of statistical evidence, it becomes increasingly incredible to suppose that a positive verdict would be impermissible. I suggest that none of the dominant views in the literature can easily accommodate such cases, and close by offering a diagnosis of my own. (shrink)

This essay is an accessible introduction to the proof paradox in legal epistemology. -/- In 1902 the Supreme Judicial Court of Maine filed an influential legal verdict. The judge claimed that in order to find a defendant culpable, the plaintiff “must adduce evidence other than a majority of chances”. The judge thereby claimed that bare statistical evidence does not suffice for legal proof. -/- In this essay I first motivate the claim that bare statistical evidence does not suffice (...) for legal proof. I then introduce and motivate a knowledge-centred explanation of this fact. The knowledge-centred explanation rests on two premises. The first is that legal proof requires knowledge of culpability. The second is that one cannot attain knowledge that p from bare statistical evidence that p. To motivate the second premise, I suggest that beliefs based on bare statistical evidence fail to be safe—they could easily be wrong—and bare statistical evidence cannot eliminate relevant alternatives. -/- I then cast doubt on the first premise; I argue that legal proof does not require knowledge. I thereby dispute the knowledge-centred explanation of the inadequacy of bare statistical evidence for legal proof. Instead of appealing to the nature of knowledge, I suggest we should seek a more direct explanation by appealing to those more foundational epistemic properties, such as safety or eliminating relevant alternatives. (shrink)

This paper defends the heretical view that, at least in some cases, we ought to assign legal liability based on purely statistical evidence. The argument draws on prominent civil law litigation concerning pharmaceutical negligence and asbestos-poisoning. The overall aim is to illustrate moral pitfalls that result from supposing that it is never appropriate to rely on bare statistics when settling a legal dispute.

Recent years have seen fresh impetus brought to debates about the proper role of statistical evidence in the law. Recent work largely centres on a set of puzzles known as the ‘proof paradox’. While these puzzles may initially seem academic, they have important ramifications for the law: raising key conceptual questions about legal proof, and practical questions about DNA evidence. This article introduces the proof paradox, why we should care about it, and new work attempting to resolve it.

For the past half-century, both jurisprudence and epistemology have been haunted by questions about why individual evidence (i.e., evidence which picks out a specific individual) can sufficiently justify a guilty or liable verdict while bare statistical evidence (i.e., statistical evidence which does not pick out a specific individual) does not sufficiently justify such a verdict. This thesis examines three popular justifications for such a disparity in verdicts – Judith Jarvis Thomson’s causal account, Enoch et al.’s sensitivity account, and Sarah (...) Moss’ knowledge-first account, before critiquing each in turn. After such an analysis, the thesis then defends the claim that legal verdicts require the factfinder (e.g., the judge or jury) to have a justified de re belief (i.e., a belief about a specific object – namely the defendant), and that this doxastic requirement justifies the disparity in rulings, as it is epistemically insufficient to justify a de re belief based on bare statistical evidence alone. A brief account of how these beliefs are formed and spread is also given. After making such a distinction, the thesis then formalizes the burdens of proof of the preponderance of the evidence and beyond a reasonable doubt using the de re/de dicto distinction. Finally, the thesis pre-empts possible objections, namely by providing an account of DNA evidence as individual evidence and giving an account of how false convictions can occur on the de re view of legal proof. (shrink)

Despite the changes in human behaviour and interactions occasioned by the COVID-19 pandemic, many institutions are yet to adapt to the new normal fully. While some educational institutions switched entirely to e-learning to promote teaching and learning, others could not offer education due to physical and social restrictions. Previous studies in Africa have identified reasons for the poor ICT adoption for educational purposes. However, the degree to which these factors affect ICT utilisation is barely analysed. Using a quantitative approach, this (...) study assessed ICT deployment for teaching in the COVID-19 era by focusing on their availability and challenges. A sample of 344 respondents from a population of 2,867 academic staff at two Nigerian public universities participated in the study. After receiving face validity from experts, a structured questionnaire was used for data collection. Cronbach alpha reliability indices of the questionnaire ranged from 0.72 to 0.94. Descriptive statistics (simple percentages, mean, and standard deviation) and inferential statistics (one-way ANOVA) were used for data analysis. Findings generally revealed a moderate extent in the availability of ICT resources in public universities. The cost of data, computer literacy, and electricity supply are challenges that significantly affected ICT deployment in the COVID-19 era. Based on this finding, it was concluded that personal and institutional challenges affect how ICT resources are deployed in public universities. It was recommended, among other things, that the management of each tertiary institution should apportion proceeds from internally generated revenue to procure ICT resources specific to the need of the school. The study provides the ground for further research into students’ use of ICT for educational purposes. (shrink)

In this paper, I first introduce one of the most prominent objections against the Growing Block Theory of time (GBT), the so-called ‘epistemic objection’, according to which GBT provides no way of knowing that our time is the objective present and, therefore, leads at best to absolute skepticism about our temporal location, at worst to the quasi-certainty that we are located in the objective past. Secondly, I express my dissatisfaction regarding the various traditional attempts to address this objection, especially Merricks (...) (2006), Forrest (2004) and Correia and Rosenkranz (2018). Thirdly, I show that the passage of time leads to an anti-essentialist picture of natural kinds. Finally, I develop my own solution to the epistemic objection, based on the continued existence of bare particulars. (shrink)

My general aim in this paper is to shed light on the controversial concept of a bare particular. I do so by arguing that bare particulars are best understood in terms of the individuative work they do within the framework of a realist constituent ontology. I argue that outside such a framework, it is not clear that the notion of a bare particular is either motivated or coherent. This is suggested by reflection on standard objections to (...) class='Hi'>bare particulars. However, within the framework of a realist constituent ontology, bare particulars provide for a coherent theory of individuation—one with a potentially significant theoretical price tag, but one that also has advantages over rival theories. (shrink)

One of the traditional desiderata for a metaphysical theory of laws of nature is that it be able to explain natural regularities. Some philosophers have postulated governing laws to fill this explanatory role. Recently, however, many have attempted to explain natural regularities without appealing to governing laws. Suppose that some fundamental properties are bare dispositions. In virtue of their dispositional nature, these properties must be (or are likely to be) distributed in regular patterns. Thus it would appear that an (...) ontology including bare dispositions can dispense with governing laws of nature. I believe that there is a problem with this line of reasoning. In this essay, I’ll argue that governing laws are indispensable for the explanation of a special sort of natural regularity: those holding among categorical properties (or, as I’ll call them, categorical regularities). This has the potential to be a serious objection to the denial of governing laws, since there may be good reasons to believe that observed regularities are categorical regularities. (shrink)

Bare particulars tend to get a bad rap. But often, the arguments lodged against bare particulars seem to miss important aspects of the theoretical context of bare particulars. In particular, these arguments fail to situate bare particulars within a constituent ontology with substrates, and thus fail to appreciate an important consequence of that context: the need for two types of exemplification. In this paper, I do three things. First, I motivate and describe the need, given (...) class='Hi'>bare particulars, for two types of exemplification, and explore more generally how constituent ontologies with substrates ought to think about exemplification. Second, I show how Andrew Bailey’s (2012) new argument against bare particulars fails when that need is charitably considered. Third, I highlight where bare particular theory ought to be pressed, which turns out to be precisely its account of exemplification. (shrink)

Bare plural generic sentences pervade ordinary talk. And yet it is extremely controversial what semantics to assign to such sentences. In this paper, I achieve two tasks. First, I develop a novel classification of the various standard uses to which bare plurals may be put. This “variety data” is important—it gives rise to much of the difficulty in systematically theorizing about bare plurals. Second, I develop a novel account of bare plurals, the radical account. On this (...) account, all bare plurals fail to express propositions. The content of a bare plural has to be pragmatically “completed” by a speaker in order for her to make an assertion. At least the content of a quantifier expression has to be supplied. But sometimes, the content of a sentential operator or modal verb is also supplied. The radical account straightforwardly explains the variety data: Speakers’ communicative intentions vary wildly across different contexts. (shrink)

This chapter will review selected aspects of the terrain of discussions about probabilities in statistical mechanics (with no pretensions to exhaustiveness, though the major issues will be touched upon), and will argue for a number of claims. None of the claims to be defended is entirely original, but all deserve emphasis. The first, and least controversial, is that probabilistic notions are needed to make sense of statistical mechanics. The reason for this is the same reason that convinced Maxwell, Gibbs, and (...) Boltzmann that probabilities would be needed, namely, that the second law of thermodynamics, which in its original formulation says that certain processes are impossible, must, on the kinetic theory, be replaced by a weaker formulation according to which what the original version deems impossible is merely improbable. Second is that we ought not take the standard measures invoked in equilibrium statistical mechanics as giving, in any sense, the correct probabilities about microstates of the system. We can settle for a much weaker claim: that the probabilities for outcomes of experiments yielded by the standard distributions are effectively the same as those yielded by any distribution that we should take as a representing probabilities over microstates. Lastly, (and most controversially): in asking about the status of probabilities in statistical mechanics, the familiar dichotomy between epistemic probabilities (credences, or degrees of belief) and ontic (physical) probabilities is insufficient; the concept of probability that is best suited to the needs of statistical mechanics is one that combines epistemic and physical considerations. (shrink)

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. (shrink)

We criticize the bare theory of quantum mechanics -- a theory on which the Schrödinger equation is universally valid, and standard way of thinking about superpositions is correct.

The law views with suspicion statistical evidence, even evidence that is probabilistically on a par with direct, individual evidence that the law is in no way suspicious of. But it has proved remarkably hard to either justify this suspicion, or to debunk it. In this paper, we connect the discussion of statistical evidence to broader epistemological discussions of similar phenomena. We highlight Sensitivity – the requirement that a belief be counterfactually sensitive to the truth in a specific way – as (...) a way of epistemically explaining the legal suspicion towards statistical evidence. Still, we do not think of this as a satisfactory vindication of the reluctance to rely on statistical evidence. Knowledge – and Sensitivity, and indeed epistemology in general – are of little, if any, legal value. Instead, we tell an incentive-based story vindicating the suspicion towards statistical evidence. We conclude by showing that the epistemological story and the incentive-based story are closely and interestingly related, and by offering initial thoughts about the role of statistical evidence in morality. (shrink)

Statistical evidence—say, that 95% of your co-workers badmouth each other—can never render resenting your colleague appropriate, in the way that other evidence (say, the testimony of a reliable friend) can. The problem of statistical resentment is to explain why. We put the problem of statistical resentment in several wider contexts: The context of the problem of statistical evidence in legal theory; the epistemological context—with problems like the lottery paradox for knowledge, epistemic impurism and doxastic wrongdoing; and the context of a (...) wider set of examples of responses and attitudes that seem not to be appropriately groundable in statistical evidence. Regrettably, we do not come up with a fully general, fully adequate, fully unified account of all the phenomena discussed. But we give reasons to believe that no such account is forthcoming, and we sketch a somewhat messier account that may be the best that can be had here. (shrink)

A popular informal argument suggests that statistics about the preponderance of criminal involvement among particular demographic groups partially justify others in making defensive mistakes against members of the group. One could worry that evidence-relative accounts of moral rights vindicate this argument. After constructing the strongest form of this objection, I offer several replies: most demographic statistics face an unmet challenge from reference class problems, even those that meet it fail to ground non-negligible conditional probabilities, even if they did, (...) they introduce new costs likely to cancel out any justificatory contribution of the statistic, but even if they didn’t, demographic facts are the wrong sort to make a moral difference to agents’ negative rights. I conclude that the popular argument should be rejected, and evidence-relative theories do not have the worrisome implication. (shrink)

Predictive algorithms are playing an increasingly prominent role in society, being used to predict recidivism, loan repayment, job performance, and so on. With this increasing influence has come an increasing concern with the ways in which they might be unfair or biased against individuals in virtue of their race, gender, or, more generally, their group membership. Many purported criteria of algorithmic fairness concern statistical relationships between the algorithm’s predictions and the actual outcomes, for instance requiring that the rate of false (...) positives be equal across the relevant groups. We might seek to ensure that algorithms satisfy all of these purported fairness criteria. But a series of impossibility results shows that this is impossible, unless base rates are equal across the relevant groups. What are we to make of these pessimistic results? I argue that none of the purported criteria, except for a calibration criterion, are necessary conditions for fairness, on the grounds that they can all be simultaneously violated by a manifestly fair and uniquely optimal predictive algorithm, even when base rates are equal. I conclude with some general reflections on algorithmic fairness. (shrink)

Brief essay on Giorgio Agamben's concept of "bare life" from Homo Sacer: Sovereign Power and Bare Life (1998), with reference to The Time that Remains: A Commentary on the Letter to the Romans (2005).

An argument to the effect that, under a few reasonable assumptions, the bare particular ontology is best understood in terms of supersubstativalism: objects are identical to regions of space(-time) and properties directly inhere in space(-time) points or region as their bearers.

It is one thing to hold that merely statistical evidence is _sometimes_ insufficient for rational belief, as in typical lottery and profiling cases. It is another thing to hold that merely statistical evidence is _always_ insufficient for rational belief. Indeed, there are cases where statistical evidence plainly does justify belief. This project develops a dispositional account of the normativity of statistical evidence, where the dispositions that ground justifying statistical evidence are connected to the goals (= proper function) of objects. There (...) are strong intuitive motivations for doing this. For we can turn almost any case of _non-justifying_ merely statistical evidence into a case of _justifying_ merely statistical evidence by adding information about the dispositions and goals of the objects involved. The resulting view not only helps us understand when and why merely statistical evidence is normatively significant, but it also helps us understand how statistical evidence relates to more standard forms of evidence (perceptual, testimonial). The emerging view also has surprising applications, as it imposes limitations on the epistemic value of fine-tuning arguments for theism as well as undermines a standard class of case-based arguments for moral encroachment. (shrink)

Causation is a macroscopic phenomenon. The temporal asymmetry displayed by causation must somehow emerge along with other asymmetric macroscopic phenomena like entropy increase and the arrow of radiation. I shall approach this issue by considering ‘causal inference’ techniques that allow causal relations to be inferred from sets of observed correlations. I shall show that these techniques are best explained by a reduction of causation to structures of equations with probabilistically independent exogenous terms. This exogenous probabilistic independence imposes a recursive order (...) on these equations and a consequent distinction between dependent and independent variables that lines up with the temporal asymmetry of causation. (shrink)

Initially introduced to the philosophical world as elusive, we-know-notwhats—substrata underlying the properties had or exemplified by things, but themselves bereft of properties—bare particulars have been dismissed as undetectable, unnecessary, and even incoherent. Hardly a warm welcome. It appears, however, that times are changing. In a recent series of articles, for example, J. P. Moreland has argued that “bare particulars are crucial entities in any adequate overall theory of individuation”;’ that is, concrete particulars cannot be individuated without them. In (...) the same vein, Oaklander and Rothstein,2 drawing upon elements of Moreland’s new theory, have defended bare particulars against Loux’s grounding objection’—that if the theory is correct, bare particulars are qualitatively indiscernible; in which case we either have no basis for saying that they arc numerically diverse, or we must introduce lower-level substrata to ground that diversity, thereby raising the spectre of an infinite regress of individuators. (shrink)

I argue against the claim, advanced by David Albert and Barry Loewer, that all non-fundamental laws can be derived from those required to underwrite the second law of thermodynamics.

In this paper I propose an interpretation of classical statistical mechanics that centers on taking seriously the idea that probability measures represent complete states of statistical mechanical systems. I show how this leads naturally to the idea that the stochasticity of statistical mechanics is associated directly with the observables of the theory rather than with the microstates (as traditional accounts would have it). The usual assumption that microstates are representationally significant in the theory is therefore dispensable, a consequence which suggests (...) interesting possibilities for developing non-equilibrium statistical mechanics and investigating inter-theoretic answers to the foundational questions of statistical mechanics. (shrink)

The article explores the striking coincidences in Heidegger's and Blanchot's account of the image as death mask. The analysis of the respective theories of the image brings forth two radically divergent conceptions of thinking as "laying patent" (Heidegger) and of thinking as "laying bare" (Blanchot).

The origins of testing scientific models with statistical techniques go back to 18th century mathematics. However, the modern theory of statistical testing was primarily developed through the work of Sir R.A. Fisher, Jerzy Neyman, and Egon Pearson in the inter-war period. Some of Fisher's papers on testing were published in economics journals (Fisher, 1923, 1935) and exerted a notable influence on the discipline. The development of econometrics and the rise of quantitative economic models in the mid-20th century made statistical significance (...) testing a commonplace, albeit controversial tool within economics. -/- In the debate about significance testing, methodological controversies intertwine with epistemological issues and sociological developments. Our aim in this chapter is to expound these connections and to show how the use of, and the debate about, significance testing in economics differs from other social sciences, such as psychology. (shrink)

Many philosophers have pointed out that statistical evidence, or at least some forms of it, lack desirable epistemic or non-epistemic properties, and that this should make us wary of litigations in which the case against the defendant rests in whole or in part on statistical evidence. Others have responded that such broad reservations about statistical evidence are overly restrictive since appellate courts have expressed nuanced views about statistical evidence. In an effort to clarify and reconcile, I put forward an interpretive (...) analysis of why statistical evidence should raise concerns in some cases but not others. I argue that when there is a mismatch between the specificity of the evidence and the expected specificity of the accusation, statistical evidence—as any other kind of evidence—should be considered insufficient to sustain a conviction. I rely on different stylized court cases to illustrate the explanatory power of this analysis. (shrink)

One finds, in Maxwell's writings on thermodynamics and statistical physics, a conception of the nature of these subjects that differs in interesting ways from the way that they are usually conceived. In particular, though—in agreement with the currently accepted view—Maxwell maintains that the second law of thermodynamics, as originally conceived, cannot be strictly true, the replacement he proposes is different from the version accepted by most physicists today. The modification of the second law accepted by most physicists is a probabilistic (...) one: although statistical fluctuations will result in occasional spontaneous differences in temperature or pressure, there is no way to predictably and reliably harness these to produce large violations of the original version of the second law. Maxwell advocates a version of the second law that is strictly weaker; the validity of even this probabilistic version is of limited scope, limited to situations in which we are dealing with large numbers of molecules en masse and have no ability to manipulate individual molecules. Connected with this is his concept of the thermodynamic concepts of heat, work, and entropy; on the Maxwellian view, these are concepts that must be relativized to the means we have available for gathering information about and manipulating physical systems. The Maxwellian view is one that deserves serious consideration in discussions of the foundation of statistical mechanics. It has relevance for the project of recovering thermodynamics from statistical mechanics because, in such a project, it matters which version of the second law we are trying to recover. (shrink)

The replication crisis has prompted many to call for statistical reform within the psychological sciences. Here we examine issues within Frequentist statistics that may have led to the replication crisis, and we examine the alternative—Bayesian statistics—that many have suggested as a replacement. The Frequentist approach and the Bayesian approach offer radically different perspectives on evidence and inference with the Frequentist approach prioritising error control and the Bayesian approach offering a formal method for quantifying the relative strength of evidence (...) for hypotheses. We suggest that rather than mere statistical reform, what is needed is a better understanding of the different modes of statistical inference and a better understanding of how statistical inference relates to scientific inference. (shrink)

This is the published version of a talk on meta-ontology in a conference of a multidisciplinary research project on "logic and sensibility". It argues against univocalism about "existence" and for a variety of perspectivism.

This paper discusses and evaluates a recent argument for the conclusion that an attractive variety of Russellian monism ought to be regarded as a form of physicalism. According to this line of thought, if the Russellian’s “inscrutable” properties are held to ground not only experience, but also the physical structure of the world—and in this sense are not “experience-specific”—they thereby have an unproblematic place in physicalist metaphysics. I argue, in contrast, that there can be a sense in which the Russellian’s (...) inscrutables are experience-specific in a way that a physicalist probably ought to find objectionable, even if they play some role other than grounding experience. This will be the case, I argue, if certain worlds are taken to be possible, as they sometimes have: worlds of “bare structure” and worlds with what might be called “swapped inscrutables”. In this way, I claim that accepting certain possibilities has consequences for how one should understand the nature of the Russellian’s inscrutables and the place they have in physicalist metaphysics. (shrink)

The application of statistical methods and models both in the natural and social sciences is nowadays a trivial fact which nobody would deny. Bold analogies even suggest the application of the same statistical models to fields as different as statistical mechanics and economics, among them the case of the young and controversial discipline of Econophysics . Less trivial, however, is the answer to the philosophical question, which has been raised ever since the possibility of “commuting” statistical thinking and models between (...) natural and social sciences emerged: whether such a methodological kinship would imply some kind of more profound unity of the natural and the social domain. Starting with Adolphe Quetelet (1796-1874) and ending with the Vienna Circle (from the late 1920s until the 1940s), this paper offers a brief historical and philosophical reconstruction of some important stages in the development of statistics as “commuting” between the natural and the social sciences. This reconstruction is meant to highlight (with respect to the authors under consideration): (1) the existence of a significant correlation between the readiness to “transfer” statistical thinking from natural to social sciences and vice versa, on the one hand, and the standpoints on the issue of the unity/disunity of science, on the other; (2) the historical roots and the fortunes of the analogy between statistical models of society and statistical models of gases. (shrink)

Statistical evidence is crucial throughout disparate impact’s three-stage analysis: during (1) the plaintiff’s prima facie demonstration of a policy’s disparate impact; (2) the defendant’s job-related business necessity defense of the discriminatory policy; and (3) the plaintiff’s demonstration of an alternative policy without the same discriminatory impact. The circuit courts are split on a vital question about the “practical significance” of statistics at Stage 1: Are “small” impacts legally insignificant? For example, is an employment policy that causes a one percent (...) disparate impact an appropriate policy for redress through disparate impact litigation? This circuit split calls for a comprehensive analysis of practical significance testing across disparate impact’s stages. Importantly, courts and commentators use “practical significance” ambiguously between two aspects of practical significance: the magnitude of an effect and confidence in statistical evidence. For example, at Stage 1 courts might ask whether statistical evidence supports a disparate impact (a confidence inquiry) and whether such an impact is large enough to be legally relevant (a magnitude inquiry). Disparate impact’s texts, purposes, and controlling interpretations are consistent with confidence inquires at all three stages, but not magnitude inquiries. Specifically, magnitude inquiries are inappropriate at Stages 1 and 3—there is no discriminatory impact or reduction too small or subtle for the purposes of the disparate impact analysis. Magnitude inquiries are appropriate at Stage 2, when an employer defends a discriminatory policy on the basis of its job-related business necessity. (shrink)

Statistical mechanics is a strange theory. Its aims are debated, its methods are contested, its main claims have never been fully proven, and their very truth is challenged, yet at the same time, it enjoys huge empirical success and gives us the feeling that we understand important phenomena. What is this weird theory, exactly? Statistical mechanics is the name of the ongoing attempt to apply mechanics, together with some auxiliary hypotheses, to explain and predict certain phenomena, above all those described (...) by thermodynamics. This paper shows what parts of this objective can be achieved with mechanics by itself. It thus clarifies what roles remain for the auxiliary assumptions that are needed to achieve the rest of the desiderata. Those auxiliary hypotheses are described in another paper in this journal, Foundations of statistical mechanics: The auxiliary hypotheses. (shrink)

At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we are in (...) a situation where the VC theorem can be applied for the purpose we want it to. (shrink)

Recently, Jennifer Saul (“Racial Figleaves, the Shifting Boundaries of the Permissible, and the Rise of Donald Trump”, 2017; “Racist and Sexist Figleaves”, 2021) has explored the use of what she calls “figleaves” in the discourse on race and gender. Following Saul, a figleaf is an utterance that, for some portion of the audience, blocks the conclusion that some other utterance, R, or the person who uttered R is racist or sexist. Such racial and gender figleaves are pernicious, says Saul, because, (...) among other things, they can shift the boundaries of what is deemed acceptable to think or say. This paper expands on Saul’s picture in a threefold way: It is first argued that appeals to statistics can function as figleaves. It is then argued that—as far as figleaves go—there is reason to believe that statistics-as-figleaves are especially pernicious. Finally, the paper explores some strategies for counterspeech. (shrink)

In this paper, we prove that Neutrosophic Statistics is more general than Interval Statistics, since it may deal with all types of indeterminacies (with respect to the data, inferential procedures, probability distributions, graphical representations, etc.), it allows the reduction of indeterminacy, and it uses the neutrosophic probability that is more general than imprecise and classical probabilities and has more detailed corresponding probability density functions. While Interval Statistics only deals with indeterminacy that can be represented by intervals. And (...) we respond to the arguments by Woodall et al. [1]. We show that not all indeterminacies (uncertainties) may be represented by intervals. Also, in some cases, we should better use hesitant sets (that have less indeterminacy) instead of intervals. We redirect the authors to the Plithogenic Probability and Plithogenic Statistics which are the most general forms of MultiVariate Probability and Multivariate Statistics respectively (including, of course, the Imprecise Probability and Interval Statistics as subclasses). (shrink)

'Mindfulness' is arguably the most important concept to have transplanted from Buddhist thought to contemporary Western psychology. However, whilst mindfulness was already an ambiguous term in the original context, specified more by a set of practices than by a clear definition, its cross-cultural transmission has blurred its content even further. In this paper, I assess the recent criticism of the widespread definition of mindfulness as non-elaborative, purely receptive 'bare attention'. According to the critics of bare attention, what can (...) be characterized as purely receptive is the automatic turning of attention toward an object. But should mindfulness be a quality of consciousness that is to be established and developed by the reflexive practice of meditation, it must be something more than this automatic turning of attention. This paper shows how the definition of mindfulness as bare attention can be defended by explicating it in terms of the phenomenological model of attention. (shrink)

In statistics, there are two main paradigms: classical and Bayesian statistics. The purpose of this article is to investigate the extent to which classicists and Bayesians can agree. My conclusion is that, in certain situations, they cannot. The upshot is that, if we assume that the classicist is not allowed to have a higher degree of belief in a null hypothesis after he has rejected it than before, then he has to either have trivial or incoherent credences to (...) begin with or fail to update his credences by conditionalization. (shrink)

Statistical mechanics is often taken to be the paradigm of a successful inter-theoretic reduction, which explains the high-level phenomena (primarily those described by thermodynamics) by using the fundamental theories of physics together with some auxiliary hypotheses. In my view, the scope of statistical mechanics is wider since it is the type-identity physicalist account of all the special sciences. But in this chapter, I focus on the more traditional and less controversial domain of this theory, namely, that of explaining the thermodynamic (...) phenomena.What are the fundamental theories that are taken to explain the thermodynamic phenomena? The lively research into the foundations of classical statistical mechanics suggests that using classical mechanics to explain the thermodynamic phenomena is fruitful. Strictly speaking, in contemporary physics, classical mechanics is considered to be false. Since classical mechanics preserves certain explanatory and predictive aspects of the true fundamental theories, it can be successfully applied in certain cases. In other circumstances, classical mechanics has to be replaced by quantum mechanics. In this chapter I ask the following two questions: I) How does quantum statistical mechanics differ from classical statistical mechanics? How are the well-known differences between the two fundamental theories reflected in the statistical mechanical account of high-level phenomena? II) How does quantum statistical mechanics differ from quantum mechanics simpliciter? To make our main points I need to only consider non-relativistic quantum mechanics. Most of the ideas described and addressed in this chapter hold irrespective of the choice of a (so-called) interpretation of quantum mechanics, and so I will mention interpretations only when the differences between them are important to the matter discussed. (shrink)

This paper puts forward the hypothesis that the distinctive features of quantum statistics are exclusively determined by the nature of the properties it describes. In particular, all statistically relevant properties of identical quantum particles in many-particle systems are conjectured to be irreducible, ‘inherent’ properties only belonging to the whole system. This allows one to explain quantum statistics without endorsing the ‘Received View’ that particles are non-individuals, or postulating that quantum systems obey peculiar probability distributions, or assuming that there (...) are primitive restrictions on the range of states accessible to such systems. With this, the need for an unambiguously metaphysical explanation of certain physical facts is acknowledged and satisfied. (shrink)

The Generality Problem is widely recognized to be a serious problem for reliabilist theories of justification. James R. Beebe's Statistical Solution is one of only a handful of attempted solutions that has garnered serious attention in the literature. In their recent response to Beebe, Julien Dutant and Erik J. Olsson successfully refute Beebe's Statistical Solution. This paper presents a New Statistical Solution that countenances Dutant and Olsson's objections, dodges the serious problems that trouble rival solutions, and retains the theoretical virtues (...) that made Beebe's solution so attractive in the first place. There indeed exists a principled, rigorous, conceptually sparse, and plausible solution to the Generality Problem: it is the New Statistical Solution. (shrink)

Kopeikin (forthcoming a, forthcoming b) and Rachels’ (1975) bare-difference cases elicit the intuition that killing is no different than letting die. Hill’s (2018) bare-difference cases elicit the intuition that killing is worse than letting die. At least one of the intuitions must be mistaken. This calls for an error theory. Hill has an error theory for the intuition elicited by the Kopeikin/Rachels’ cases. Kopeikin and Rachels have an error theory for the intuition elicited by Hill’s cases. A natural (...) thought is that we are at an impasse. There is no plausible basis for preferring one error theory to the other. I argue that this natural thought is mistaken. Not all error theories are equal. Preliminary considerations favor Hill’s error theory and disfavor the Kopeikin/Rachels error theory. But preliminary considerations are not decisive. The way forward in the bare-difference debate is not to evaluate intuitions. The intuitions are in. What is left to do now is evaluate the comparative status of the Hill and the Kopeikin/Rachels error theories. (shrink)