As machine learning informs increasingly consequential decisions, different metrics have been proposed for measuring algorithmic bias or unfairness. Two popular “fairness measures” are calibration and equality of false positive rate. Each measure seems intuitively important, but notably, it is usually impossible to satisfy both measures. For this reason, a large literature in machine learning speaks of a “fairness tradeoff” between these two measures. This framing assumes that both measures are, in fact, capturing something important. To date, philosophers have (...) seldom examined this crucial assumption, and examined to what extent each measure actually tracks a normatively important property. This makes this inevitable statistical conflict – between calibration and false positive rate equality – an important topic for ethics. In this paper, I give an ethical framework for thinking about these measures and argue that, contrary to initial appearances, false positive rate equality is in fact morally irrelevant and does not measure fairness. (shrink)

Objective: To determine if the medical record might overestimate the quality of care through false, and potentially unethical, documentation by physicians.Design: Prospective trial comparing two methods for measuring the quality of care for four common outpatient conditions: structured reports by standardised patients who presented unannounced to the physicians’ clinics, and abstraction of the medical records generated during these visits.Setting: The general medicine clinics of two veterans affairs medical centres.Participants: Twenty randomly selected physicians from among eligible second and third year (...) internal medicine residents and attending physicians.Main measurements: Explicit criteria were used to score the medical records of physicians and the reports of SPs generated during 160 visits . Individual scoring items were categorised into four domains of clinical performance: history, physical examination, treatment, and diagnosis. To determine the false positive rate, physician entries were classified as false positive , false negative, true positive, and true negative.Results: False positives were identified in the medical record for 6.4% of measured items. The false positive rate was higher for physical examination and diagnosis than for history and treatment . For individual physician subjects, the false positive rate ranged from 0.098 to 0.397.Conclusions: These data indicate that the medical record falsely overestimates the quality of important dimensions of care such as the physical examination. Though it is doubtful that most subjects in our study participated in regular, intentional falsification, we cannot exclude the possibility that false positives were in some instances intentional, and therefore fraudulent, misrepresentations. Further research is needed to explore the questions raised but incompletely answered by this research. (shrink)

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I (...) error rates. I begin with an introduction to Type I error rates that distinguishes them from theoretical errors. I then illustrate my argument with respect to model misspecification, multiple testing, selective inference, forking paths, exploratory analyses, p-hacking, optional stopping, double dipping, and HARKing. In each case, I demonstrate that relevant Type I error rates are not usually inflated above their nominal level, and in the rare cases that they are, the inflation is easily identified and resolved. I conclude that the replication crisis may be explained, at least in part, by researchers’ misinterpretation of statistical errors and their underestimation of theoretical errors. (shrink)

This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that (...) constitute deductive calculations based on known probabilities among events. As a result, the ampliative dimension of frequentist induction—learning from data about the underlying data-generating mechanism—is missing. *Received August 2009; revised January 2010. †To contact the author, please write to: Department of Economics, Virginia Tech, Blacksburg, VA 24061; e-mail: [email protected]. (shrink)

In the context of discovery-oriented hypothesis testing research, behavioral scientists widely accept a convention for false positive (α) and false negative error rates (β) proposed by Jacob Cohen, who deemed the general relative seriousness of the antecedently accepted α = 0.05 to be matched by β = 0.20. Cohen’s convention not only ignores contexts of hypothesis testing where the more serious error is the β-error. Cohen’s convention also implies for discovery-oriented hypothesis testing research that a statistically (...) significant observed effect is four times more probable to be a mistaken discovery than for a statistically significant true observed effect to be independently replicable. In the long run, Cohen’s convention thus is epistemically harmful to the development of a progressive science of human behavior, making its acceptance crucial in explaining the replication crisis in behavioral science. The balance between α- and β-errors generally ought to be struck using both epistemic and practical considerations. Yet epistemic considerations alone imply that making a genuine contribution to the body of knowledge in behavioral science requires error rates that are not only small but also symmetrical. (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 (...) class='Hi'>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)

The Securities and Exchange Commission (SEC) sanctioned investor-paid rating agency Egan-Jones for falsely stating that it did not know its clients’ investment positions. The SEC’s action against Egan-Jones raises the broad question whether knowledge of clients’ investment positions creates a conflict of interest for investor-paid ratings. In an experimental setting, we find that investor-paid rating agencies are likely to assign credit ratings that are biased in favor of their clients’ positions, and that this effect is attenuated when the rated company (...) has a sophisticated investor base that is expected to scrutinize ratings. The effect is not conditional on the risk profile of the rated companies. Taken together, our findings suggest that a conflict of interest stemming from investors’ preferences is likely to bias ratings under investor-pays business models, but scrutiny by the company’s investor base can counteract this bias. (shrink)

A pair of studies demonstrates that simply asking children to make a blatantly false accusation in the guise of helping others can result in both immediate and long-term false claims. In the pilot study, the initial willingness to make a blatantly false statement was associated with some children making false statements a week later despite being told that the first interviewer had made mistakes during the initial interview. On a positive note, the majority of participants (...) accurately stated that they did not have first-hand knowledge of their accusation's accuracy. Across both studies, the rate of false accusation rates was high. The main experiment demonstrated that children who were young, possessed the lowest verbal intelligence or who were from the lowest SES homes made the most accusations. These findings illustrate not only the dangers of encouraging children to make false statements, but the ease and durability of making such false statements. (shrink)

Current symptom-based DSM and ICD diagnostic criteria for mental disorders are prone to yielding false positives because they ignore the context of symptoms. This is often seen as a benign flaw because problems of living and emotional suffering, even if not true disorders, may benefit from support and treatment. However, diagnosis of a disorder in our society has many ramifications not only for treatment choice but for broader social reactions to the diagnosed individual. In particular, mental disorders impose a (...) sick role on individuals and place a burden upon them to change; thus, disorders decrease the level of respect and acceptance generally accorded to those with even annoying normal variations in traits and features. Thus, minimizing false positives is important to a pluralistic society. The harmful dysfunction analysis of disorder is used to diagnose the sources of likely false positives, and propose potential remedies to the current weaknesses in the validity of diagnostic criteria. (shrink)

The question whether memory aberrations in posttraumatic stress disorder also manifest as an increased production of false memories is important for both theoretical and practical reasons, but is yet unsolved. Therefore, for the present study we investigated veridical and false recognition in PTSD with a new scenic variant of the Deese–Roediger–McDermott paradigm, which was administered to traumatized individuals with PTSD , traumatized individuals without PTSD , and non-traumatized controls . The PTSD group neither produced higher rates of (...) false memories nor expressed more confidence in errors, but did show inferior memory sensitivity. Whereas depressive symptoms did not correlate with veridical nor false recognition, state dissociation was positively associated with false memories. (shrink)

Recent debates in psychopathy studies have articulated concerns about false-positives in assessment and research sampling. These are pressing concerns for research progress, since scientific quality depends on sample quality, that is, if we wish to study psychopathy we must be certain that the individuals we study are, in fact, psychopaths. Thus, if conventional assessment tools yield substantial false-positives, this would explain why central research is laden with discrepancies and nonreplicable findings. This paper draws on moral psychology in order (...) to develop tentative theory-driven exclusion criteria applicable in research sampling. Implementing standardized procedures to discriminate between research participants has the potential to yield more homogenous and discrete samples, a vital prerequisite for research progress in etiology, epidemiology, and treatment strategies. (shrink)

E-commerce sites have been doing profitable business since their induction in high-speed and secured networks. Moreover, they continue to influence consumers through various methods. One of the most effective methods is the e-commerce review rating system, in which consumers provide review ratings for the products used. However, almost all e-commerce review rating systems are unable to provide cumulative review ratings. Furthermore, review ratings are influenced by positive and negative malicious feedback ratings, collectively called false reviews. In this paper, (...) we proposed an e-commerce review system framework developed using the cumulative sum method to detect and remove malicious review ratings. (shrink)

ICD-10 and DSM-5 do not provide clear diagnosing guidelines for DID, making it difficult to distinguish ‘genuine’ DID from imitated or false-positive cases. This study explores meaning which patients with false-positive or imitated DID attributed to their diagnosis. 85 people who reported elevated levels of dissociative symptoms in SDQ-20 participated in clinical assessment using the Trauma and Dissociation Symptoms Interview, followed by a psychiatric interview. The recordings of six women, whose earlier DID diagnosis was disconfirmed, were (...) transcribed and subjected to interpretative phenomenological analysis. Five main themes were identified: endorsement and identification with the diagnosis. The notion of dissociative parts justifies identity confusion and conflicting ego-states. Gaining knowledge about DID affects the clinical presentation. Fragmented personality becomes an important discussion topic with others. Ruling out DID leads to disappointment or anger. To avoid misdiagnoses, clinicians should receive more systematic training in the assessment of dissociative disorders, enabling them to better understand subtle differences in the quality of symptoms and how dissociative and non-dissociative patients report them. This would lead to a better understanding of how patients with and without a dissociative disorder report core dissociative symptoms. Some guidelines for a differential diagnosis are provided. (shrink)

Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned – that is, that the two must refer to roughly the same set of hypothetical observations. Here, I argue that many applications of statistical inference in psychology fail to meet this basic condition. Focusing on the most widely used (...) class of model in psychology – the linear mixed model – I explore the consequences of failing to statistically operationalize verbal hypotheses in a way that respects researchers' actual generalization intentions. I demonstrate that although the “random effect” formalism is used pervasively in psychology to model intersubject variability, few researchers accord the same treatment to other variables they clearly intend to generalize over. The under-specification of random effects imposes far stronger constraints on the generalizability of results than most researchers appreciate. Ignoring these constraints can dramatically inflate false-positive rates, and often leads researchers to draw sweeping verbal generalizations that lack a meaningful connection to the statistical quantities they are putatively based on. I argue that failure to take the alignment between verbal and statistical expressions seriously lies at the heart of many of psychology's ongoing problems, and conclude with a discussion of several potential avenues for improvement. (shrink)

Volume 26, Issue 3, September 2020, Page 284-286.

Nair-Collins and Joffe (2023) rightly call attention to an incompatibility between brain-based criteria for death, as defined by the Uniform Determination of Death Act (UDDA), and what the current...

Some patients who have been diagnosed as “dead by neurologic criteria” continue to exhibit certain brain functions, most commonly, neuroendocrine functions. This preservation of neurologic function after the diagnosis of “brain death” or “brainstem death” is an ongoing source of controversy and concern in the medical, bioethics, and legal literatures. Most obviously, if some brain function persists, then it is not the case that all functions of the entire brain have ceased and hence, declaring such a patient to be “dead” (...) would be a false positive, in any nation with so-called “whole brain death” laws. Furthermore, and perhaps more concerning, the preservation of any brain function necessarily entails the preservation of some amount of brain perfusion, thereby raising the concern as to whether additional areas of neural tissue may remain viable, including areas in the brainstem. These and other considerations cast significant doubt on the reliability of diagnosing either “brain death” or “brainstem death.”. (shrink)

Background: Noninvasive prenatal testing (NIPT) is a new prenatal screening technology that became commercially available in the United States in 2011. NIPT's increased accuracy and low false positive rate compared to previous screening methods enable many women to avoid invasive diagnostic testing and receive much desired reassurance. NIPT has received much attention for both its benefits and drawbacks. Methods: Observation of genetic counseling sessions and qualitative interviews with women offered NIPT at a large academic medical center were conducted. (...) Two ethnographic cases studies derived from the overall data set are used to illustrate the study findings. Results: Many fundamental ethical questions about prenatal screening, such as abortion or the value of disabled children, often do not emerge during clinical sessions, enabling most women to defer thinking about these issues until the future, when and if the need should arise. It may only be in the rare case when a woman receives a positive test result that she may be forced to confront ethical issues that she had up until then been able to avoid. Conclusions: Women want, and are grateful to have, access to NIPT, which offers much desired reassurance. This desire for reassurance may come at the expense of having contemplated the potential negative outcomes and limitations of testing. In the rare circumstance where women do not receive reassuring results, they may be unprepared and shocked by what NIPT can and cannot reveal. The routinization of NIPT as the latest and best available prenatal screening test does not necessarily create new ethical issues, but this study highlights ethical continuities following its arrival. However, the continued expansion of NIPT to include more conditions and women will increase the number of women who receive positive results, including false positives, and who may be shocked and unprepared as a result. (shrink)

In the recent literature on confirmation there are two leading approaches to the provision of a probabilistic measure of the degree to which a hypothesis is confirmed by evidence. The first is to construe the degree to which evidence E confirms hypothesis H as a function that is directly proportional to p and inversely proportional to p . I shall refer to this as the probability approach. The second approach construes the notion as a function that is directly proportional to (...) the true-positive rate – the probability of the evidence if the hypothesis is true, p – and inversely proportional to the false-positive rate – the probability of the evidence if the hypothesis is false, p . These reverse conditional probabilities – of the evidence on the truth or falsehood of the hypothesis – are sometimes known as likelihoods. I shall refer to the approach to confirmation that uses them as the likelihood approach.For each of these approaches, there are two obvious options as to how to define the confirmation function. The first is to define it as the difference between the magnitude that is treated as increasing confirmation or p ) and the magnitude that is treated as decreasing confirmation or p ). The second is to define confirmation as the quotient of these two magnitudes.This yields four different measures of confirmation, represented in the following table: Differences RatiosProbabilities PD = p – p1 PR = Graphic2Likelihoods LD = p – p3 LR = Graphic4All these measures agree on whether or not E provides some support for H. Intuitively, we want to say that E provides some support for H just in case learning that E is true would make us assign a higher probability to H, i.e. when p(H …. (shrink)

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social (...) neuroscience that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial, but also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in SPM12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxel-wise thresholding with family-wise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods. (shrink)

McGregor and MacNamee recently, in this journal, offered several criticisms of an earlier article in which I attempted to refute a number of arguments for the claim that doping in sports is morally wrong. Their criticisms are numerous, but focus on four domains. First, they sketch a view on which the risk profiles of different sports may make doping permissible in some and impermissible in others. Second, they suggest that my criticisms of safety-based arguments assume that doping opponents are bent (...) on harm elimination, rather than harm management. Finally, they offer two methodological criticisms, the first pertaining to my use of analogical arguments, and the second pertaining to the general difficulties of making revisionist arguments in ethics. I defend my criticisms of safety-based arguments by showing that these do not rest on the assumptions McGregor and MacNamee attribute to me and by noting that their own view about the variable relevance of safety considerations is underdeveloped. As for their methodological arguments, I endeavor to show that these are misplaced, in that they either rest on misinterpretations of my earlier article or on an excessively high standard for ethical argumentation. (shrink)

Under the “Willful Ignorance Principle,” a defendant is guilty of a crime requiring knowledge he lacks provided he is ignorant thanks to having earlier omitted inquiry. In this paper, I offer a novel justification of this principle through application of the theory that knowledge matters to culpability because of how the knowing action manifests the agent’s failure to grant sufficient weight to other people’s interests. I show that, under a simple formal model that supports this theory, omitting inquiry manifests precisely (...) the same degree of disregard of others’ interests as manifested in knowingly acting criminally. Several surprising implications of this view are described, including that when the agent’s method of inquiry has a non-zero false positive rate, his omission of inquiry does not make the same contribution to his culpability as knowledge, while it does, by contrast, when the false negative rate is non-zero. (shrink)

Type 1: This process occurs for half of the population. For this segment of the population, there is 10% chance of developing the disease. There is a test for the disease such that 90% of the people who have the disease in this case will test positive (event E), while the false positive rate is 10%, which means that there is a 10% chance of testing positive for the disease when they do not have the disease.

Visual aids can improve comprehension of risks associated with medical treatments, screenings, and lifestyles. Do visual aids also help decision makers accurately assess their risk comprehension? That is, do visual aids help them become well calibrated? To address these questions, we investigated the benefits of visual aids displaying numerical information and measured accuracy of self-assessment of diagnostic inferences (i.e., metacognitive judgment calibration) controlling for individual differences in numeracy. Participants included 108 patients who made diagnostic inferences about three medical tests on (...) the basis of information about the sensitivity and false-positive rate of the tests and disease prevalence. Half of the patients received the information in numbers without a visual aid, while the other half received numbers along with a grid representing the numerical information. In the numerical condition, many patients --especially those with low numeracy-- misinterpreted the predictive value of the tests and profoundly overestimated the accuracy of their inferences. Metacognitive judgment calibration mediated the relationship between numeracy and accuracy of diagnostic inferences. In contrast, in the visual aid condition, patients at all levels of numeracy showed high-levels of inferential accuracy and metacognitive judgment calibration. Results indicate that accurate metacognitive assessment may explain the beneficial effects of visual aids and numeracy --a result that accords with theory suggesting that metacognition is an essential part of risk literacy. We conclude that well-designed risk communications can inform patients about health-relevant numerical information while helping them assess the quality of their own risk comprehension. (shrink)

In the last decade, many problematic cases of scientific conduct have been diagnosed; some of which involve outright fraud others are more subtle. These and similar problems can be interpreted as caused by lack of scientific objectivity. The current philosophical theories of objectivity do not provide scientists with conceptualizations that can be effectively put into practice in remedying these issues. We propose a novel way of thinking about objectivity for individual scientists; a negative and dynamic approach.We provide a philosophical conceptualization (...) of objectivity that is informed by empirical research. In particular, it is our intention to take the first steps in providing an empirically and methodologically informed inventory of factors that impair the scientific practice. The inventory will be compiled into a negative conceptualization, which could in principle be used by individual scientists to assess objectivity of scientific practice. We propose a preliminary outline of a usable and testable instrument for indicating the objectivity of scientific practice. (shrink)

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo with (...) the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

Contemporary Artificial Intelligence methods, especially their subset-deep learning, are finding their way to successful implementations in the detection and classification of intrusions at the network level. This paper presents an intrusion detection mechanism that leverages Deep AutoEncoder and several Deep Decoders for unsupervised classification. This work incorporates multiple network topology setups for comparative studies. The efficiency of the proposed topologies is validated on two established benchmark datasets: UNSW-NB15 and NetML-2020. The results of their analysis are discussed in terms of classification (...) accuracy, detection rate, false-positive rate, negative predictive value, Matthews correlation coefficient and F1-score. Furthermore, comparing against the state-of-the-art methods used for network intrusion detection is also disclosed. (shrink)

Spam electronic mails (emails) refer to harmful and unwanted commercial emails sent to corporate bodies or individuals to cause harm. Even though such mails are often used for advertising services and products, they sometimes contain links to malware or phishing hosting websites through which private information can be stolen. This study shows how the adaptive intelligent learning approach, based on the visual anti-spam model for multi-natural language, can be used to detect abnormal situations effectively. The application of this approach is (...) for spam filtering. With adaptive intelligent learning, high performance is achieved alongside a low false detection rate. There are three main phases through which the approach functions intelligently to ascertain if an email is legitimate based on the knowledge that has been gathered previously during the course of training. The proposed approach includes two models to identify the phishing emails. The first model has proposed to identify the type of the language. New trainable model based on Naive Bayes classifier has also been proposed. The proposed model is trained on three types of languages (Arabic, English and Chinese) and the trained model has used to identify the language type and use the label for the next model. The second model has been built by using two classes (phishing and normal email for each language) as a training data. The second trained model (Naive Bayes classifier) has been applied to identify the phishing emails as a final decision for the proposed approach. The proposed strategy is implemented using the Java environments and JADE agent platform. The testing of the performance of the AIA learning model involved the use of a dataset that is made up of 2,000 emails, and the results proved the efficiency of the model in accurately detecting and filtering a wide range of spam emails. The results of our study suggest that the Naive Bayes classifier performed ideally when tested on a database that has the biggest estimate (having a general accuracy of 98.4%, false positive rate of 0.08%, and false negative rate of 2.90%). This indicates that our Naive Bayes classifier algorithm will work viably on the off chance, connected to a real-world database, which is more common but not the largest. (shrink)

The current WSN is vulnerable to a variety of malicious attacks, resulting in the decline of its comprehensive performance. Multihop routing involves a number of safety and privacy issues. Problems such as snooping, sinkhole, manipulation, cloning, wormhole, spoofing, and so on affect the integrity, availability, and confidentiality of the WSNs. Therefore, this paper mainly studies the mathematical modeling of WSN multiattack behavior discrimination based on the incidence matrix. The WSN node model is used to collect relevant data and mark and (...) map the disguised data, so as to determine the characteristics of multiattack behavior and establish the WSN multiattack behavior discrimination model based on the incidence matrix. The experimental results show that the designed multiattack behavior discrimination model can distinguish the attack type according to the characteristics, has high recognition ability, can spend a short time to effectively distinguish the attack behavior, has a low false positive rate, and can effectively improve the antiattack ability of the WSN. (shrink)

In this paper, I defend epistemological contrastivism—the view that propositional knowledge is a three-place, contrastive relation between an agent, a proposition and a contrast term—against two a priori arguments recently offered by Mikkel Gerken for the conclusion that intuitive judgements exhibiting a contrast effect on knowledge ascriptions are false positives. I show that the epistemic argument for false positives begs the question against contrastivism by assuming the independently implausible claim that knowledge of a contrastive proposition always presupposes knowledge (...) of a related ordinary proposition. This claim is apparently also presupposed by the doxastic argument for false positives, the conclusion of which, I argue, is not only perfectly compatible with epistemological contrastivism but also heavily dependent on a de dicto construal of the relevant knowledge ascriptions. (shrink)

Before the recent presidential election, a bipartisan congressional effort was made to pass a criminal justice reform bill. The bill faltered in part because of a proposed default mens rea provision: statutes silent on mens rea, that were not explicitly identified as strict liability by the legislature, would be taken to require for guilt proof of knowledge with respect to each material element. This paper focusses on a prominent line of disagreement about the default mens rea provision. Proponents argued that (...) it would reduce the number of unjust verdicts in corporate cases. They noted that there have been convictions of corporations and corporate officers for public welfare offenses in instances in which there was good reason to believe that the defendants lacked mens rea. They touted the legislation, then, as a way of reducing the false positive rate. Opponents noted that the provision would also reduce the rate of true positives in corporate prosecutions—convictions of those possessing mens rea who could not be proven to—and opposed the legislation on those grounds. Both sides, then, accepted that the relevant question was, in part, numerical: under the provision, would the reductions in guilty verdicts of those lacking mens rea outnumber and outweigh the increases in acquittals of those possessing it? This paper critically examines this numerical approach for assessing and justifying the default mens rea provision. The paper argues that there is a small domain under which it is appropriate to reason in such numerical terms about a default mens rea provision, but that that domain is so small as to make such arguments inappropriate when it comes to sweeping legislation, such as that proposed. The paper further argues that in light of this conclusion the default mens rea provision must be examined non-numerically, through appeal to principled considerations about the necessary conditions for morally justified infliction of punishment. When such arguments are freed from numerical considerations of the kind that dominated the public discussion of the legislation, they decide the matter: the default mens rea provision deserves bipartisan support. (shrink)

Atrial fibrillation is the most common cardiac arrhythmia in clinical practice. It often starts with asymptomatic and short episodes, which are difficult to detect without the assistance of automatic monitoring tools. The vast majority of methods proposed for this purpose are based on quantifying the irregular ventricular response during the arrhythmia. However, although AF totally alters the atrial activity reflected on the electrocardiogram, replacing stable P-waves by chaotic and time-variant fibrillatory waves, this information has still not been explored for automated (...) screening of AF. Hence, a pioneering AF detector based on quantifying the variability over time of the AA morphological pattern is here proposed. Results from two public reference databases have proven that the proposed method outperforms current state-of-the-art algorithms, reporting accuracy higher than 90%. A less false positive rate in the presence of other arrhythmias different from AF was also noticed. Finally, the combination of this algorithm with the classical analysis of RR series variability also yielded a promising trade-off between AF accuracy and detection delay. Indeed, this combination provided similar accuracy than RR-based methods, but with a significantly shorter delay of 10 beats. (shrink)

Jeff Nisker describes his personal experience of a diagnosis of advanced prostate cancer and the kindnesses he received from friendly doctors. He claims that this narrative account supports the promotion of Prostate Specific Antigen screening for asymptomatic men and impugns statisticians, mistakenly thinking that their opposition to PSA screening derives from concerns about financial cost. The account inadvertently demonstrates the danger of over-reliance on a single ethical tool for critical analysis. In the first part of this response, we describe the (...) statistical evidence. The most reliable Cochrane meta-analyses have not shown that PSA screening saves lives overall. Moreover, the high false positive rate of PSA screening leads to overinvestigation which results in unnecessary anxiety and increased cases of unnecessary sepsis, urinary incontinence and sexual dysfunction. Then we describe how narrative ethics alone is an insufficient tool to make claims about policies, such as PSA screening, which have hidden harms. Although Nisker’s story-telling is compelling and evokes emotions, narrative ethics of this sort have an inherent bias against people who would be harmed by the counterfactual. Particular care must be taken to look for and consider those untellable stories. Ethicists who only consider narratives which are readily at hand risk harming those who are voiceless or protected by the status quo. PSA screening is the wrong tool to reduce prostate cancer deaths and narrative ethics is the wrong tool to appraise this policy. It is vital that the correct theoretical tools are applied to the medical and ethical questions under scrutiny. (shrink)

We demonstrate how different normalization techniques in GC‐MS analysis impart unique properties to the data, influencing any biological inference. Using simulations, and empirical data, we compare the most commonly used techniques (Total Sum Normalization ‘TSN’; Median Normalization ‘MN’; Probabilistic Quotient Normalization ‘PQN’; Internal Standard Normalization ‘ISN’; External Standard Normalization ‘ESN’; and a compositional data approach ‘CODA’). When differences between biological classes are pronounced, ESN and ISN provides good results, but are less reliable for more subtly differentiated groups. MN, TSN, and (...) CODA approaches produced variable results dependent on the structure of the data, and are prone to false positive biomarker identification. In contrast, PQN exhibits the lowest false positive rate, though with occasionally poor model performance. Because ESN requires extensive pre‐planning, and offers only mixed reliability, and ISN, TSN, MN, and CODA approaches are prone to introducing artefactual differences, we recommend the use of PQN in GC–MS research. (shrink)

The Quality Attestation Presidential Task Force's recent proposal for “quality attestation” (QA) of clinical ethics consultants was advanced on the premise that, “[g]iven the importance of clinical ethics consultation, the people doing it should be asked to show that they do it well.” To this end, the task force attempted to develop “a standardized system for proactively assessing the knowledge, skills, and practice of clinical ethicists.” But can this proposed method deliver? If the proposed QA process is flawed, it will (...) label clinical ethicists as qualified to do clinical ethics consultations (CECs) when they are not. The result will be the creation of a new, likely intractable, problem of CEC “false positives:” consultants who have passed QA without actually possessing the requisite knowledge and skills to perform CECs.To avoid the risk of false positives, the QAPTF needs to conduct a rigorous analysis of the skills that the QA process will be positioned to judge and those that are simply beyond the scope of its current metrics. Rather than “attesting” to overall CEC “quality,” QA needs to be precise about the skill inventory it can confirm yet honest about the skills it has no basis to assess. I will argue here that QA has strong prospects for accurately assessing consultants’ competence in ethical analysis but very weak prospects for determining competence in two other skills listed as essential by the QAPTF: value‐neutrality and conflict resolution. (shrink)

PurposeThe purpose of this study was to introduce an orthogonal experimental design to improve the efficiency of building and optimizing models for freezing of gait prediction.MethodsA random forest model was developed to predict FOG by using acceleration signals and angular velocity signals to recognize possible precursor signs of FOG. An OED was introduced to optimize the feature extraction parameters.ResultsThe main effects and interaction among the feature extraction hyperparameters were analyzed. The false-positive rate, hit rate, and mean prediction time (...) were 27%, 68%, and 2.99 s, respectively.ConclusionThe OED was an effective method for analyzing the main effects and interactions among the feature extraction parameters. It was also beneficial for optimizing the feature extraction parameters of the FOG prediction model. (shrink)

We thank the authors of commentaries for their thoughtful discussion of our target article. Here we briefly summarize the points made in the target article (Nair-Collins and Joffe 2023). Then we em...