It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)

This article addresses the gap between what works in research and what works in practice. Currently, research in evidence-based education policy and practice focuses on randomized controlled trials. These can support causal ascriptions (“It worked”) but provide little basis for local effectiveness predictions (“It will work here”), which are what matter for practice. We argue that moving from ascription to prediction by way of causal generalization (“It works”) is unrealistic and urge focusing research efforts directly on how to build (...) local effectiveness predictions. We outline various kinds of information that can improve predictions and encourage using methods better equipped for acquiring that information. We compare our proposal with others advocating a better mix of methods, like implementation science, improvement science, and practice-based evidence. (shrink)

Are predictions about how one will freely and intentionally behave in the future ever relevant to how one ought to behave? There is good reason to think they are. As imperfect agents, we have responsibilities of self-management, which seem to require that we take account of the predictable ways we're liable to go wrong. I defend this conclusion against certain objections to the effect that incorporating predictions concerning one's voluntary conduct into one's practical reasoning amounts to evading responsibility for (...) that conduct. There is, however, some truth to this sort of objection. To understand the legitimate role of self-prediction in practical reasoning, we need to distinguish instances of coping responsibly with an anticipated failure to behave as one ought, on the one hand, from mere acquiescence in one's flaws, on the other. I argue that, to draw this distinction, we must recognize certain limits on the use of self-prediction as a ground of choice. (shrink)

It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)

A self-fulfilling prophecy is, roughly, a prediction that brings about its own truth. Although true predictions are hard to fault, self-fulfilling prophecies are often regarded with suspicion. In this article, we vindicate this suspicion by explaining what self-fulfilling prophecies are and what is problematic about them, paying special attention to how their problems are exacerbated through automated prediction. Our descriptive account of self-fulfilling prophecies articulates the four elements that define them. Based on this account, we begin our critique (...) by showing that typical self-fulfilling prophecies arise due to mistakes about the relationship between a prediction and its object. Such mistakes—along with other mistakes in predicting or in the larger practical endeavor—are easily overlooked when the predictions turn out true. Thus we note that self-fulfilling prophecies prompt no error signals; truth shrouds their mistakes from humans and machines alike. Consequently, self-fulfilling prophecies create several obstacles to accountability for the outcomes they produce. We conclude our critique by showing how failures of accountability, and the associated failures to make corrections, explain the connection between self-fulfilling prophecies and feedback loops. By analyzing the complex relationships between accuracy and other evaluatively significant features of predictions, this article sheds light both on the special case of self-fulfilling prophecies and on the ethics of prediction more generally. (shrink)

The quest to foretell the future is omnipresent in human affairs. A potential solution to this epistemological conundrum has emerged through mass collaboration. Motored by the Internet, prediction markets allow a multitude of individuals to assume a stake in a security whose value is tied to a future event. The resulting prices offer a continuously updated probability estimate of the event actually taking place. This paper gives a survey of prediction markets, their history, mechanics, uses, and theoretical foundation. (...) We also review the literature surrounding their efficacy. Though there are shortcomings with prediction markets, as well as practical constraints, they hold out the prospect of improving the quality of organizational decisions and increasing the level of participation in the deliberative process. We also note that lessons can be drawn from these markets to guide the epistemological practices of disciplines and inquiries in which empirical methods are difficult to apply. (shrink)

Rid and Wendler propose the development of a Patient Preference Predictor (PPP), an actuarial model for predicting incapacitated patient’s life-sustaining treatment preferences across a wide range of end-of-life scenarios. An actuarial approach to end-of-life decision making has enormous potential, but transferring the logic of actuarial prediction to end-of-life decision making raises several conceptual complexities and logistical problems that need further consideration. Actuarial models have proven effective in targeted prediction tasks, but no evidence supports their effectiveness in the kind (...) of broad spectrum prediction task that is the proposed goal of the PPP. We argue that a more focused approach, targeting specific medical conditions and generating treatment predictions based on the preferences of individuals with actual disease experience, is both more firmly grounded in past research and is a more prudent initial strategy for exploring the efficacy of actuarial prediction in end-of-life decision making. (shrink)

Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients’ values and goals of care, which often requires input from clinicians and loved ones. Although the use of algorithms to predict patients’ most likely preferred treatment has been discussed in the medical ethics literature, no example has been realised in clinical practice. This is due, arguably, to the (...) lack of a structured approach to the epistemological, ethical and pragmatic challenges arising from the design and use of such algorithms. The present paper offers a new perspective on the problem by suggesting that preference predicting AIs be viewed as sociotechnical systems with distinctive life-cycles. We explore how both known and novel challenges map onto the different stages of development, highlighting interdisciplinary strategies for their resolution. (shrink)

This study focuses on the prediction of the engagement of small- and medium-sized enterprises (SMEs) in environmental management practices, based on a random sample of 689 SMEs. The study finds that several endogenous factors, including tangibility of sector, firm size, innovative orientation, family influence and perceived financial benefits from energy conservation, predict an SME’s level of engagement in selected environmental management practices. For family influence, this effect is found only in interaction with the number of owners. In addition to (...) empirical research on SMEs’ environmental behavior, this article draws on the ecological modernization literature as well as the theory of planned behavior. (shrink)

A new theory of the mind, the predictive processing model, is ascendant in recent work in cognitive science. According to this theory, all the mind ever fundamentally does is make hypotheses about the environment, generate prediction-errors by comparing its predictions with its sensory data, and use these prediction-errors to update its representation of the world. The theory of motivation and action to which the predictive processing model is committed has been the subject of lively debate in the literature. (...) However, the upshots of the predictive processing model for the theory of practical reason have received relatively scant attention. Here I investigate how proponents of predictive processing should conceive of practical reason. The predictive processing model has it that the practical attitudes – desires and intentions etc. – reduce to certain theoretical attitudes – in particular, to beliefs and predictions. I argue that this psychological reduction precipitates a broader normative reduction, in which practical reasoning reduces to a kind of theoretical reasoning about what you will do, and in which practical normativity turns out to really be a species of epistemic normativity. In other words, that practical reason reduces to theoretical reason. If I am correct, the predictive processing model of the mind is committed to – what I am dubbing – a ‘radical cognitivism about practical reason’. (shrink)

Shared activity is often simply willed into existence by individuals. This poses a problem. Philosophical reflection suggests that shared activity involves a distinctive, interlocking structure of intentions. But it is not obvious how one can form the intention necessary for shared activity without settling what fellow participants will do and thereby compromising their agency and autonomy. One response to this problem suggests that an individual can have the requisite intention if she makes the appropriate predictions about fellow participants. I argue (...) that implementing this predictive strategy risks derailing practical reasoning and preventing one from forming the intention. My alternative proposal for reconciling shared activity with autonomy appeals to the idea of acting directly on another's intention. In particular, I appeal to the entitlement one sometimes has to another's practical judgment, and the corresponding authority the other sometimes has to settle what one is to do. (shrink)

This paper examines the practice of using predictive systems to lengthen the prison sentences of convicted persons when the systems forecast a higher likelihood of re-offense or re-arrest. There has been much critical discussion of technologies used for sentencing, including questions of bias and opacity. However, there hasn’t been a discussion of whether this use of predictive systems makes sense in the first place. We argue that it does not by showing that there is no plausible theory of punishment that (...) supports it. (shrink)

To succeed, political science usually requires either prediction or contextual historical work. Both of these methods favor explanations that are narrow-scope, applying to only one or a few cases. Because of the difficulty of prediction, the main focus of political science should often be contextual historical work. These epistemological conclusions follow from the ubiquity of causal fragility, under-determination, and noise. They tell against several practices that are widespread in the discipline: wide-scope retrospective testing, such as much large-n statistical (...) work; lack of emphasis on prediction; and resources devoted to ‘pure theory’ divorced from frequent empirical application. I illustrate, via Donatella della Porta’s work on political violence, the important role that is still left for theory. I conclude by assessing the scope for political science to offer policy advice. (shrink)

Consciousness vehicle externalism is the claim that the material machinery of a subject’s phenomenology partially leaks outside a subject’s brain, encompassing bodily and environmental structures. The DEUTS argument is the most prominent argument for CVE in the sensorimotor enactivists’ arsenal. In a recent series of publications, Kirchhoff and Kiverstein have deployed such an argument to claim that a prominent view of neural processing, namely predictive processing, is fully compatible with CVE. Indeed, in Kirchhoff and Kiverstein’s view, a proper understanding of (...) predictive processing mandates CVE. In this essay, we critically examine Kirchhoff and Kiverstein’s argument. Our aim is to argue in favor of the following three points. First, that Kirchhoff and Kiverstein’s emphasis on cultural practices lends no support to CVE: at best, it vindicates some form of content externalism about phenomenal content. Secondly, the criteria Kirchhoff and Kiverstein propose to identify a subject’s phenomenal machinery greatly overgeneralize, leaving them open to a “consciousness bloat” objection, which is an analog of the cognitive bloat objection against the extended mind. Lastly, we will argue that the “consciousness bloat” problem is inbuilt in the very argumentative structure of the DEUTS argument. We will thus conclude that, contrary to the philosophical mainstream, DEUTS is not the best argument for CVE in the sensorimotor enactivists’ argumentative arsenal. (shrink)

Recent neo-Humean theories of laws of nature have placed substantial emphasis on the characteristic epistemic roles played by laws in scientific practice. In particular, these theories seek to understand laws in terms of their optimal predictive utility to creatures in our epistemic situation. In contrast to other approaches, this view has the distinct advantage that it is able to account for a number of pervasive features possessed by putative actual laws of nature. However, it also faces some unique challenges. First, (...) since the view tries to characterize the laws in terms of their predictive utility, any respects in which putative actual laws are sub-optimally predictively useful are inherently problematic. Such "predictive infelicities" can easily be found among our best physical theories. Second, in tying the laws to our epistemic situation, neo-Humeanism raises the possibility that by changing our epistemic situation, we can change the laws themselves, though it is hard to believe that we have such influence over the laws. This paper aims to address both of these challenges, first by presenting a variety of strategies for explaining away predictive infelicities, and then by developing a version of Lewis's "rigidification" strategy to preclude the possibility of our changing the laws. (shrink)

In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...) I develop is a version of common cause explanation. Common cause explanation has long been vindicated by appealing to the principle of the common cause. Many philosophers of science (e.g., Sober and Tucker) find this principle problematic, however, because they believe that it is either purely methodological or strictly metaphysical. I defend a third possibility: the principle of the common cause derives its justification from a physically pervasive time asymmetry of causation (a.k.a. the asymmetry of overdetermination). I argue that explicating the principle of the common cause in terms of the asymmetry of overdetermination illuminates some otherwise puzzling features of the practices of historical natural scientists. (shrink)

What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, the efficacy of medicine (...) for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine. (shrink)

Professionals often believe that they must “exercise judgment” in making decisions critical to other people’s lives. The relative superiority of statistical prediction rules to intuitive judgment for combining incomparable sources of information to predict important human outcomes leads us to question this personal input belief. Some professionals hence use SPR’s to “educate” intuitive judgment, rather than replace it. In psychology in particular, such amalgamation is not justified. If a well‐validated SPR that is superior to professional judgment exists in a (...) relevant decision making context, professionals should use it, totally absenting themselves from the prediction. (shrink)

Professionals often believe that they must “exercise judgment” in making decisions critical to other people's lives. The relative superiority of statistical prediction rules to intuitive judgment for combining incomparable sources of information to predict important human outcomes leads us to question this personal input belief. Some professionals hence use SPR's to “educate” intuitive judgment, rather than replace it. In psychology in particular, such amalgamation is not justified. If a well-validated SPR that is superior to professional judgment exists in a (...) relevant decision making context, professionals should use it, totally absenting themselves from the prediction. (shrink)

In this paper I argue that, by combining eliminativist and fictionalist approaches toward the sub-personal representational posits of predictive processing, we arrive at an empirically robust and yet metaphysically innocuous cognitive scientific framework. I begin the paper by providing a non-representational account of the five key posits of predictive processing. Then, I motivate a fictionalist approach toward the remaining indispensable representational posits of predictive processing, and explain how representation can play an epistemologically indispensable role within predictive processing explanations without thereby (...) requiring that representation metaphysically exists. Finally, I outline four consequences of accepting this approach and explain why they are beneficial: we arrive at a victory for metaphysical eliminativism in the ‘representation wars’; my account fits with extant empirical practice; my account provides guidance for future research; and, my account provides the beginnings of a response to Mark Sprevak’s IBE problem for fictionalist approaches toward sub-personal representation. (shrink)

Psychiatric diagnosis and prognosis is fraught with important philosophical and conceptual problems. This chapter focuses on some epistemological issues and moral issues that arise in contemporary psychiatric practice. It examines various clinical and actuarial techniques for psychiatric diagnosis, ordered very loosely in terms of how "structured" or "automated" they are. The chapter makes the case for assessing psychiatric treatments with controlled experiments, raises several epistemological dangers that arise from relying on uncontrolled investigations, and considers some of the unique methodological and (...) ethical issues that arise when trying to assess talk therapy. (shrink)

Predictive Sentencing addresses the role of risk assessment in contemporary sentencing practices. Predictive sentencing has become so deeply ingrained in Western criminal justice decision-making that despite early ethical discussions about selective incapacitation, it currently attracts little critique. Nor has it been subjected to a thorough normative and empirical scrutiny. This is problematic since much current policy and practice concerning risk predictions is inconsistent with mainstream theories of punishment. Moreover, predictive sentencing exacerbates discrimination and disparity in sentencing. Although structured risk assessments (...) may have replaced 'gut feelings', and have now been systematically implemented in Western justice systems, the fundamental issues and questions that surround the use of risk assessment instruments at sentencing remain unresolved. This volume critically evaluates these issues and will be of great interest to scholars of criminal justice and criminology. (shrink)

Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role (...) of orthodox economic theory. Second, a conditional predictivism: if we are not committed to orthodox economic theory, then we should demand prediction rather than accommodation – against most current practice. (shrink)

Racial capitalism depends on the reproduction of an existing racialized economic order. In this article, I argue that the disavowal of past injustice is a central way in which this reproduction is ensured and that market-based forms of knowledge production, such as for-profit predictive practices, play a crucial role in facilitating this disavowal. Recent debates about the fairness of algorithms, data justice, and predictive policing have intensified long-standing controversies, both popular and academic, about the way in which statistical and financial (...) modes of accounting and predicting articulate, represent and produce ascriptive categories of hierarchically ordered social difference, and reproduce unjust social hierarchies and inequalities. These debates have productively problematized the racial lives of seemingly apolitical predictive technologies and demanded the re-politicization of predictive practices. What has been missing from these debates so far, however, is a more explicit engagement with ways in which anti-racist movements and activists themselves have contested the entanglements of prediction and race making. I turn to a recent prominent example, namely the contestation over racial discrepancies in subprime lending to examine how fair lending activists have conceptualized and troubled the reproduction of a racialized economic order through for-profit predictive practices in the decade before the Great Financial Crisis. I situate this particular example in the broader historical and political context of politicizing prediction that first emerged with the ascendancy of a liberal, individualist-proprietary conception of risk, and the political problem space to which this has given rise. My analysis shows that actuarial conceptions of fairness continue to reverberate in anti-racist contestations of for-profit predictive practices, and that they tend to marginalize and undercut more radical strands of critique of the racialization of financial markets. Insofar as these modalities of contestation implicitly reproduce a liberal, proprietary-individualist conception of risk, I argue, they fail to effectively challenge the quasi-alchemical transformation of injustice into personal responsibility, and thus contribute to the disavowal of past injustice. (shrink)

Develops a general theory of prediction that encompasses its fundamental principles, methodology, and practice and gives an overview of its promises and problems.

_ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a (...) case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call _tendential prediction_. (shrink)

Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method (i.e. its scientificity) lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a case study empirical research on the alleged (...) empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call tendential prediction. (shrink)

Two hundred and twenty-six state employees completed a structured questionnaire that investigated their ethical values and training needs. Top management were more likely to have attitudes against cronyism and giving advantage to others. Individuals higher in the organizational hierarchy, and female employees were more likely to believe that discriminatory practices were an ethical concern. In addition, employees with a larger number of clients outside of the organization were more supportive of the need to maintain strict confidentiality in business dealings. Employees'' (...) awareness and use of the organization''s code of conduct generally proved to be poor predictors of ethical values. Other analyses revealed that a variety of sociodemographic factors, job characteristics and ethical values predicted specific areas of training needs in ethics. (shrink)

Predictive genetic testing for susceptibility to psychiatric conditions is likely to become part of standard practice. Because the onset of most psychiatric diseases is in late adolescence or early adulthood, testing minors could lead to early identification that may prevent or delay the development of these disorders. However, due to their complex aetiology, psychiatric genetic testing does not provide the immediate medical benefits that current guidelines require for testing minors. While several authors have argued non-medical benefits may play a crucial (...) role in favour of predictive testing for other conditions, little research has explored such a role in psychiatric disorders. This paper outlines the potential non-medical benefits and harms of psychiatric genetic testing in minors in order to consider whether the non-medical benefits could ever make such testing appropriate. Five non-medical themes arise in the literature: psychological impacts, autonomy/self-determination, implications of the biomedical approach, use of financial and intellectual resources, and discrimination. Non-medical benefits were prominent in all of them, suggesting that psychiatric genetic testing in minors may be appropriate in some circumstances. Further research needs to empirically assess these potential non-medical benefits, incorporate minors in the debate, and include normative reflection to evaluate the very purposes and motivations of psychiatric genetic testing in minors. (shrink)

Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method (i.e. its scientificity) lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a case study empirical research on the alleged (...) empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call tendential prediction. (shrink)

Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a case study empirical research on the alleged empirical association between (...) human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call tendential prediction. (shrink)

In recent years, the biomedical field has witnessed the emergence of novel tools and modelling techniques driven by the rise of the so-called Big Data. In this paper, we address the issue of predictability in biomedical Big Data models of cancer patients, with the aim of determining the extent to which computationally driven predictions can be implemented by medical doctors in their clinical practice. We show that for a specific class of approaches, called k-Nearest Neighbour algorithms, the ability to draw (...) predictive inferences relies on a geometrical, or topological, notion of similarity encoded in a well-defined metric, which determines how close the characteristics of distinct patients are on average. We then discuss the conditions under which the relevant models can yield reliable and trustworthy predictive outcomes. (shrink)

Among many properties distinguishing emergence, such as novelty, irreducibility and unpredictability, computational accounts of emergence in terms of computational incompressibility aim first at making sense of such unpredictability. Those accounts prove to be more objective than usual accounts in terms of levels of mereology, which often face objections of being too epistemic. The present paper defends computational accounts against some objections, and develops what such notions bring to the usual idea of unpredictability. I distinguish the objective unpredictability, compatible with determinism (...) and entailed by emergence, and various possibilities of predictability at emergent levels. This makes sense of practices common in complex systems studies that forge qualitative predictions on the basis of comparisons of simulations with multiple values of parameters. I consider robustness analysis as a way to ensure the ontological character of computational emergence. Finally, I focus on the property of novelty, as it is displayed by biological evolution, and ask whether computer simulations of evolution can produce the same kind of emergence as the open-ended evolution attested in Phanerozoic records. (shrink)

What has science actually achieved? A theory of achievement should define what has been achieved, describe the means or methods used in science, and explain how such methods lead to such achievements. Predictive accuracy is one truth‐related achievement of science, and there is an explanation of why common scientific practices tend to increase predictive accuracy. Akaike’s explanation for the success of AIC is limited to interpolative predictive accuracy. But therein lies the strength of the general framework, for it also provides (...) a clear formulation of many open problems of research. (shrink)

This article argues for a revised best system account of laws of nature. David Lewis’s original BSA has two main elements. On the one hand, there is the Humean base, which is the totality of particular matters of fact that obtain in the history of the universe. On the other hand, there is what I call the ‘nomic formula’, which is a particular operation that gets applied to the Humean base in order to output the laws of nature. My revised (...) account focuses on this latter element of the view. Lewis conceives of the nomic formula as a balance of simplicity and strength, but I argue that this is a mistake. Instead, I motivate and develop a different proposal for the standards that figure into the nomic formula, and I suggest a rationale for why these should be the correct standards. Specifically, I argue that the nomic formula should be conceived as a collection of desiderata designed to generate principles that are predictively useful to creatures like us. The resulting view—which I call the ‘best predictive system’ account of laws—is thus able to explain why scientists are interested in discovering the laws, and it also gives rise to laws with the sorts of features that we find in actual scientific practice 1Introduction2The LOPP3A Problem with Lewis's Formula4A Pragmatic Account of the Nomic Formula 4.1Informative dynamics4.2Wide applicability4.3Spatial locality4.4Temporal locality4.5Spatial, temporal, and rotational symmetries4.6Predictively useful properties4.7Simplicity4.8Recap5 Conclusion. (shrink)

BackgroundHaving moral courage is a crucial characteristic for nurses to handle ethical quandaries, stay true to their professional obligations towards patients, and uphold ethical principles. This concept can be influenced by various factors including personal, professional, organizational, and leadership considerations. The purpose of this study was to explore the predictors of moral courage among nurses working in hospitals.MethodsIn 2018, an observational cross-sectional study was carried out on 267 nurses employed in six hospitals located in the northern region of Iran. The (...) participants were selected through a simple random sampling technique. To collect data, a demographic information form was used along with two questionnaires. The first questionnaire was a standard survey on moral courage, while the second questionnaire was designed to assess the ethical climate. Linear regression was used to assess the predictors of moral courage.ResultsNurses had an average moral courage score of 87.07 ± 15.52 and an average moral climate score of 96.12 ± 17.17. The study showed that 16% of the variation in moral courage scores among nurses was explained by ethical climate and monthly overtime hours.ConclusionThis study underscores the significance of establishing an ethical work environment and minimizing overtime hours in order to enhance moral courage among nurses. These findings carry weight for both nursing practice and organizational policies focused on fostering ethical conduct within healthcare settings. (shrink)

What has science actually achieved? A theory of achievement should define what has been achieved, describe the means or methods used in science, and explain how such methods lead to such achievements. Predictive accuracy is one truth-related achievement of science, and there is an explanation of why common scientific practices tend to increase predictive accuracy. Akaike's explanation for the success of AIC is limited to interpolative predictive accuracy. But therein lies the strength of the general framework, for it also provides (...) a clear formulation of many open problems of research. (shrink)

A common type of inductive problem is to predict the nature of an unobserved finite sample of a given population on the basis of an observed finite sample of the same population. More precisely, given a class of events A, we examine a sample Sn having n members, of which mi belong to the class Bi. On the basis of our knowledge that mi/n of Sn have been Bi, we attempt to predict the ratio of members of Bi to members (...) of A in a sample Sr containing r unobserved members of A. This type of inference has been called “predictive inference” by Carnap. It is not necessary to argue that all inductive problems reduce to this form; we merely observe that such problems frequently arise, and that they have practical and theoretical importance. In The Short Run I suggested that this kind of problem could be handled by first determining the long run probability P of Bi, relative to A of Bi, to A in the observed sample Sn) and then predicting that the relative frequency of Bi within the unobserved sample Sr will approximate P sufficiently for practical purposes. The foregoing procedure requires a rule of each of two types: a rule for the ascertainment of the values of long run probabilities, and a rule for the application of knowledge of long run probabilities to predictions in the short run. The Short Run was not concerned with the nature and justification of rules of the first type, but rather sought to justify a rule of the second type on the assumption that we already possess knowledge of long run probabilities. (shrink)

This study aims to examine the main determinants of efficiency of both conventional and Islamic Saudi banks and then choose the best fit model among machine learning prediction models, Chi-squared automatic interaction detector, linear regression, and neural network ). The data were collected from the annual financial reports of Saudi banks from 2014 to 2018. The Saudi banking sector consists of 11 banks, 4 of which are Islamic. In this study, the major financial ratios are subgrouped into the profitability (...) ratios, managerial practices, asset and loans, capital adequacy ratios, and liquidity. First, regression analysis is implemented with efficiency ratio as a dependent variable and the proxies of banks’ profitability, liquidity, asset quality, management ratios, and capital adequacy ratios as independent variables. Next, the feature selection is applied for different prediction models. Subsequently, 4 prediction models were developed to choose the best fit. The performance metrics have also been evaluated. Regression results exhibit that the efficiency of both conventional and Islamic banks is highly affected by profitability, liquidity, and managerial practices. Finally, we choose the best prediction model with the highest R2 in the training and the testing phases with/out feature selection that is the CHAID model. The best predictors of cost efficiency for Saudi banks are the capital ratios, namely, CAR total and CAR tier 1. Findings are theoretically and practically important to academics, investors, and policymakers. Policymakers can benefit from the novelty of this study in building an early warning system using the CHAID model to predict different financial distress scenarios. (shrink)

: In this paper I argue that belief in the greater confirmatory value of prediction over accommodation can best be understood as a function of the practice rather than the logic of science. Attempts to account for this asymmetry within the logic of science have revealed no non-arbitrary way to address the problem of underdetermination as it applies to prediction and thus have failed to account for the preference for prediction over accommodation on logical grounds. Instead, I (...) propose a model that not only justifies and explains this preference, but allows for a richer taxonomy of the types of evidential confirmation that are employed in scientific reasoning. (shrink)

The considerations set out in the paper are intended to suggest that in practical contexts predictive power does not play the outstanding roles sometimes accredited to it in an epistemic framework. Rather, predictive power is part of a network of other merits and achievements. Predictive power needs to be judged differently according to the specific conditions that apply. First, predictions need to be part of an explanatory framework if they are supposed to guide actions reliably. Second, in scientific expertise, (...) the demand for accurate predictions is replaced with the objective of specifying a robust corridor of estimates. Finally, it is highly uncertain to predict the success of research projects. The overall purpose of the paper is to enlarge the debate about predictions by addressing specifically the roles of predictions in application-oriented research. (shrink)

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The (...) experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: the performance of the minority of participants who did not find boundedly optimal adaptations, and the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training. (shrink)