Autism spectrum disorder is an inherited long-living and neurological disorder that starts in the early age of childhood with complicated causes. Autism spectrum disorder can lead to mental disorders such as anxiety, miscommunication, and limited repetitive interest. If the autism spectrum disorder is detected in the early childhood, it will be very beneficial for children to enhance their mental health level. In this study, different machine and deep learning algorithms were applied to classify the severity of autism spectrum disorder. Moreover, (...) different optimization techniques were employed to enhance the performance. The deep neural network performed better when compared with other approaches. (shrink)

In 1990, Gilles Deleuze publishedPostscript on the Societies of Control, an introduction to the potentially suffocating reality of the nascent control society. This thirty-year update details how Deleuze’s conception has developed from a broad speculative vision into specific economic mechanisms clustering around personal information, big data, predictive analytics, and marketing. The central claim is that today’s advancing control society coerces without prohibitions, and through incentives that are not grim but enjoyable, even euphoric because they compel individuals to obey (...) their own personal information. The article concludes by delineating two strategies for living that are as unexplored as control society itself because they are revealed and then enabled by the particular method of oppression that is control. (shrink)

In this paper, we explore how the development and affordances of predictive analytics may impact how teachers and other educational actors think about and teach students and, more broadly, how society understands education. Our particular focus is on the data dashboards of learning support systems which are based on Machine Learning. While previous research has focused on how these systems produce credible knowledge, we explore here how they also produce compelling, persuasive and convincing narratives. Our main argument is (...) that particular kinds of stories are written by predictive analytics and written into their data dashboards. Based on a case study of a leading predictive analytics system, we explore how data dashboards imply causality between the ‘facts’ they are visualising. To do so, we analyse the stories they tell according to their spatial and temporal dimensions, characters and events, sequentiality as well as tellability. In the stories we identify, teachers are managers, students are at greater or lesser risk, and students’ sociality is reduced to machine-readable interactions. Overall, only data marked as individual behaviours becomes relevant to the system, rendering structural inequalities invisible. Reflecting on the implications of these systems, we suggest ways in which the uptake of these systems can interrupt such stories and reshape them in other directions. (shrink)

Data analytics and data-driven approaches in Machine Learning are now among the most hailed computing technologies in many industrial domains. One major application is predictive analytics, which is used to predict sensitive attributes, future behavior, or cost, risk and utility functions associated with target groups or individuals based on large sets of behavioral and usage data. This paper stresses the severe ethical and data protection implications of predictive analytics if it is used to predict sensitive (...) information about single individuals or treat individuals differently based on the data many unrelated individuals provided. To tackle these concerns in an applied ethics, first, the paper introduces the concept of “predictive privacy” to formulate an ethical principle protecting individuals and groups against differential treatment based on Machine Learning and Big Data analytics. Secondly, it analyses the typical data processing cycle of predictive systems to provide a step-by-step discussion of ethical implications, locating occurrences of predictive privacy violations. Thirdly, the paper sheds light on what is qualitatively new in the way predictive analytics challenges ethical principles such as human dignity and the (liberal) notion of individual privacy. These new challenges arise when predictive systems transform statistical inferences, which provide knowledge about the cohort of training data donors, into individual predictions, thereby crossing what I call the “prediction gap”. Finally, the paper summarizes that data protection in the age of predictive analytics is a collective matter as we face situations where an individual’s (or group’s) privacy is violated using dataotherindividuals provide about themselves, possibly even anonymously. (shrink)

An analytic cognitive style denotes a propensity to set aside highly salient intuitions when engaging in problem solving. We assess the hypothesis that an analytic cognitive style is associated with a history of questioning, altering, and rejecting supernatural claims, both religious and paranormal. In two studies, we examined associations of God beliefs, religious engagement, conventional religious beliefs and paranormal beliefs with performance measures of cognitive ability and analytic cognitive style. An analytic cognitive style negatively predicted both religious and paranormal beliefs (...) when controlling for cognitive ability as well as religious engagement, sex, age, political ideology, and education. Participants more willing to engage in analytic reasoning were less likely to endorse supernatural beliefs. Further, an association between analytic cognitive style and religious engagement was mediated by religious beliefs, suggesting that an analytic cognitive style negatively affects religious engagement via lower acceptance of conventional religious beliefs. Results for types of God belief indicate that the association between an analytic cognitive style and God beliefs is more nuanced than mere acceptance and rejection, but also includes adopting less conventional God beliefs, such as Pantheism or Deism. Our data are consistent with the idea that two people who share the same cognitive ability, education, political ideology, sex, age and level of religious engagement can acquire very different sets of beliefs about the world if they differ in their propensity to think analytically. (shrink)

Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the (...) patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. (shrink)

Confirmed COVID-19 cases in the United States increased exponentially, quickly leading to a pandemic in 2020, which created a serious public-health emergency. During the period in which the COVID-1...

Currently, most studies are moving towards Big Data Analytics because they are important in research, and this is becoming increasingly important as Internet and Web 2.0 technologies become increasingly popular and how to handle this massive data. Moreover, this proliferation of the Internet and social media has revolutionized the search process. With this Big Data of data generated by users using social media or electronic platforms, the use of these details and daily activities is integrated with tools designed for (...) analysis. The topic of analyzing big social media will be discussed and an intensive explanation will be given to the topic of Big Data. This paper compares Big Data analysis techniques using several methods of analysis, the first technique using neural networks and the second technique using data clustering. The purpose of this study is to infer the ages that use social media and what are their interests in writing and in the end, who are the most widely used social media males or females. (shrink)

The medical profession is steeped in traditions that guide its practice. These traditions were developed to preserve the well-being of patients. Transformations in science, technology, and society, while maintaining a self-governance structure that drives the goal of care provision, have remained hallmarks of the profession. The purpose of this paper is to examine ethical challenges in health care as it relates to Big Data, Accountable Care Organizations, and Health Care Predictive Analytics using the principles of biomedical ethics laid (...) out by Beauchamp and Childress. Among these are the use of Electronic Health Records within stipulations of the Health Insurance Portability and Accountability Act. Clinicians are well-positioned to impact health policy development to address ethical issues associated with the use of Big Data, Accountable Care, and Health Care Predictive Analytics as we work to transform the doctor–patient relationship towards improving population health outcomes and creating a healthier society. (shrink)

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and (...) academics have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented... (shrink)

Connected vehicle fleets have formed significant component of industrial internet of things scenarios as part of Industry 4.0 worldwide. The number of vehicles in these fleets has grown at a steady pace. The vehicles monitoring with machine learning algorithms has significantly improved maintenance activities. Predictive maintenance potential has increased where machines are controlled through networked smart devices. Here, benefits are accrued considering uptimes optimization. This has resulted in reduction of associated time and labor costs. It has also provided significant (...) increase in cost benefit ratios. Considering vehicle fault trends in this research predictive maintenance problem is addressed through hybrid deep learning-based ensemble method (HDLEM). The ensemble framework which acts as predictive analytics engine comprises of three deep learning algorithms viz modified cox proportional hazard deep learning (MCoxPHDL), modified deep learning embedded semi supervised learning (MDLeSSL) and merged LSTM (MLSTM) networks. Both sensor as well as historical maintenance data are collected and prepared using benchmarking methods for HDLEM training and testing. Here, times between failures (TBF) modeling and prediction on multi-source data are successfully achieved. The results obtained are compared with stated deep learning models. This ensemble framework offers great potential towards achieving more profitable, efficient and sustainable vehicle fleet management solutions. This helps better telematics data implementation which ensures preventative management towards desired solution. The ensemble method's superiority is highlighted through several experimental results. (shrink)

Two decades ago, the introduction of the Implicit Association Test (IAT) sparked enthusiastic reactions. With implicit measures like the IAT, researchers hoped to finally be able to bridge the gap between self-reported attitudes on one hand and behavior on the other. Twenty years of research and several meta-analyses later, however, we have to conclude that neither the IAT nor its derivatives have fulfilled these expectations. Their predictive value for behavioral criteria is weak and their incremental validity over and above (...) self-report measures is negligible. In our review, we present an overview of explanations for these unsatisfactory findings and delineate promising ways forward. Over the years, several reasons for the IAT’s weak predictive validity have been proposed. They point to four potentially problematic features: First, the IAT is by no means a pure measure of individual differences in associations but suffers from extraneous influences like recoding. Hence, the predictive validity of IAT-scores should not be confused with the predictive validity of associations. Second, with the IAT, we usually aim to measure evaluation (“liking”) instead of motivation (“wanting”). Yet, behavior might be determined much more often by the latter than the former. Third, the IAT focuses on measuring associations instead of propositional beliefs and thus taps into a construct that might be too unspecific to account for behavior. Finally, studies on predictive validity are often characterized by a mismatch between predictor and criterion (e.g., while behavior is highly context-specific, the IAT usually takes into account neither situation nor domain). Recent research, however, also revealed advances addressing each of these problems, namely (1) procedural and analytical advances to control for recoding in the IAT, (2) measurement procedures to assess implicit wanting, (3) measurement procedures to assess implicit beliefs, and (4) approaches to increase the fit between implicit measures and behavioral criteria (e.g., by incorporating contextual information). Implicit measures like the IAT hold an enormous potential. In order to allow them to fulfill this potential, however, we have to refine our understanding of these measures, and we should incorporate recent conceptual and methodological advancements. This review provides specific recommendations on how to do so. (shrink)

In this paper, I discuss the strong thesis of cognitive penetrability (CPs), to wit, th at the perceptual states (P) of a subject (S) are pervasively influenced, affected, or caused by cognitive factors (C) as expectations, memories, thoughts, goals, and so on, at all levels of perceptual processing. I argue that following the predictive coding models of perception (PC), the strong thesis of cognitive penetrability is to be expected.

Emotions play a prominent role in social life, yet the direct impact of emotions on behavior and judgment remains a point of disagreement. The current investigation used meta-analysis to test two theoretical perspectives. The emotion-as-direct-causation perspective asserts that current emotions guide behavior and judgment, whereas the emotion-as-feedback perspective asserts that anticipated emotions guide behavior and judgment. Although the emotion-as-direct-causation perspective was frequently tested, only 22% of tests were significant. Although the emotion-as-feedback perspective was rarely tested, 87% of tests were significant. (...) Our findings suggest that empirical evidence is weak for the default assumption that emotion is the proximal cause of behavior and judgment. Our preliminary findings also suggest that anticipated emotion reliably impacts social behavior and judgment. (shrink)

Making more accurate marketing decisions by managers requires building effective predictive models. Typically, these models specify the probability of customer belonging to a particular category, group or segment. The analytical CRM categories refer to customers interested in starting cooperation with the company, customers who purchase additional products or customers intending to resign from the cooperation. During building predictive models researchers use analytical tools from various disciplines with an emphasis on their best performance. This article attempts to build a (...) hybrid predictive model combining decision trees and cluster analysis. During experiments five different cluster validity indices and eight datasets were used. The performance of models was evaluated by using popular measures such as: accuracy, precision, recall, G-mean, F-measure and lift in the first and in the second decile. The authors tried to find a connection between the number of clusters and models' quality. (shrink)

Three studies investigated implicit brand attitudes and their relation to explicit attitudes, prod- uct usage, and product differentiation. Implicit attitudes were measured using the Implicit As- sociation Test (IAT; Greenwald, McGhee, & Schwartz, 1998). Study 1 showed expected differ- ences in implicit attitudes between users of two leading yogurt brands, also revealing significant correlations between IAT-measured implicit attitudes and explicit attitudes. In Study 2, users of two fast food restaurants (McDonald’s and Milk Bar) showed implicit attitudi- nal preference for their (...) favorite restaurant. In Study 3, implicit attitudes of users of two soft drinks (Coca-Cola and Pepsi) predicted brand preference, product usage, and brand recognition in a blind taste test. A meta-analytic combination of the three studies showed that the use of IAT measures increased the prediction of behavior relative to explicit attitude measures alone. (shrink)

Forecasting involves an underlying conceptualization of probability. It is this that gives sense to the notion of precision in number that makes us think of economic forecasting as more than simply complicated guesswork. We think of it as well-founded statement, a science and not an art of numbers. However, this understanding is at odds with the nature of social reality and the attributes of the forecaster. We should think differently about how we both anticipate and make the future and what (...) this means. Foresight is perhaps a more appropriate term. This paper addresses two issues that rarely receive attention in the field of economics. First, why is there a continued high demand for economic forecasts despite their lack of success in anticipating significant turning points in any given system? Second, what are forecasts actually assuming about the nature of a system and the future state of the world? In the paper I approach these issues indirectly. My intention is to highlight their significance by setting out a series of arguments that encapsulate the characteristics of a forecaster required to match a common understanding of what forecasting is intended to do. The structure of this paper is unusual for a contribution in the field of economics. It follows a format more commonly used in analytical philosophy when the author wants to focus on a problem and where the intention is to provoke further questioning, rather than supply ready answers. As such, it should not be read as a comprehensive account of all possible approaches to methods or philosophies of forecasting and attendant issues of probability. Three points are worth stating at the outset as a guide to what follows: Forecasting tends to forget that it is conjecture and what that really means. Its scientism overburdens how it is articulated and how it is perceived. We tend to think of forecasting as degrees of precision in prediction and of successful prediction as successful description of phenomena at some future point. There is, as the following discussion demonstrates, something basically inconsistent within the implications of this minimalism. Since the greater part of the credibility of, and authority of, economics resides in its claims to effective forecasting these points are highly relevant to the state of the discipline. Read the Open Peer Discussion on this paper ». (shrink)

“Prediction” and “prescription” are crucial notions for economics. This paper offers a philosophical and methodological approach and takes into account the connection with the problem of science and values. To do this, two steps are followed: firstly, prediction in economics -its characteristics and limits- will be examined and, secondly, the role of prescription in economics (and its relations with internal and external values) will be studied. Thus; the underlying aims of this paper are to make explicit the characters of economic (...) prediction, to show its nexus with the economic prescription and to point out the links of both -especially, the latter- with the specific values of “economic activity” and the values of “economics as activity” (i. e., values of economic undertaking as an activity interconnected with others in the social context). (shrink)

The experimental research paradigm lies at the core of empirical psychology. New data analytical and computational tools continually enrich its methodological arsenal, while the paradigm’s mission remains the testing of theoretical predictions and causal explanations. Predictions regarding experimental results necessarily point to the future. Once the data are collected, the causal inferences refer to a hypothesis now lying in the past. The experimental paradigm is not designed to permit strong inferences about particular incidents that occurred before predictions were made. In (...) contrast, historical research and scholarship in other humanities focus on this backward direction of inference. The disconnect between forward-looking experimental psychology and backward-looking historical (i.e., narrative) psychology is a challenge in the postmodern era, which can be addressed. To illustrate this possibility, I discuss three historical case studies in light of theory and research in contemporary psychology. (shrink)

With the progress of social production, the competition for talents among enterprises is fierce, and the market often lacks capable leaders, which leads to the lack of management of enterprise employees and cannot bring more economic benefits to enterprises. Traditional leaders make subordinate employees work actively and achieve the common goal of the enterprise by exerting their own leadership characteristics and observing their subordinates, but they cannot take care of the psychological state of each employee, resulting in the employee's work (...) efficiency is not very high. In recent years, charismatic leadership has become an important economic leader in the new era, and the theoretical spirit of charismatic leadership can well guide employees to work actively. Artificial intelligence affective computing can well identify the psychological state of the subject, and the combination of artificial intelligence affective computing and charismatic leadership can achieve effective management of employees through the predictive analysis of employees' psychological state. This paper compares the psychological state prediction analysis of employees' work attitudes between charismatic leaders based on artificial intelligence affective computing and traditional leaders through experiments. The results show that: charismatic leaders based on artificial intelligence affective computing predictive analytics can improve sensitivity to employee needs, resulting in an 8.2% increase in employee trust in leadership, a 4.4% increase in employee commitment to achieving organizational goals, and a 19.3% increase in employee job satisfaction. The psychological state prediction analysis of charismatic leaders based on artificial intelligence affective computing on employees' work attitudes can improve the work efficiency of employees and the economic benefits of enterprises. (shrink)

The paper is concerned with the psychological relevance of a logical model for deductive reasoning. We propose a new way to analyze logical reasoning in a deductive version of the Mastermind game implemented within a popular Dutch online educational learning system (Math Garden). Our main goal is to derive predictions about the difficulty of Deductive Mastermind tasks. By means of a logical analysis we derive the number of steps needed for solving these tasks (a proxy for working memory load). Our (...) model is based on the analytic tableaux method, known from proof theory. We associate the difficulty of Deductive Mastermind game-items with the size of the corresponding logical trees obtained by the tableaux method. We derive empirical hypotheses from this model. A large group of students (over 37 thousand children, 5–12 years of age) played the Deductive Mastermind game, which gave empirical difficulty ratings of all 321 game-items. The results show that our logical approach predicts these item ratings well, which supports the psychological relevance of our model. (shrink)

Can we measure and predict character with predictive analytics so a business can better assess, ideally objectively, whether to lend money or extend credit to that person, beyond current objective measures of credit scores and standard financial metrics like solvency and debt ratios? We and the analysts probably do not know enough about character to try to measure it, though it might be more useful to measure and predict a person’s temperance and prudence as virtues, or self-control as (...) psychology, or sense of obligation, particularly a moral commitment or sense of duty to honor a contract and re-pay a loan. The pervasive data surveillance of people that goes with “big data” and predictive analytics is not only an invasion of privacy in general, but an impairment of the aspect of privacy called autonomy that will constrict and alter a person’s choices and development of self. (shrink)

Predictive judicial analytics holds the promise of increasing efficiency and fairness of law. Judicial analytics can assess extra-legal factors that influence decisions. Behavioral anomalies in judicial decision-making offer an intuitive understanding of feature relevance, which can then be used for debiasing the law. A conceptual distinction between inter-judge disparities in predictions and inter-judge disparities in prediction accuracy suggests another normatively relevant criterion with regards to fairness. Predictive analytics can also be used in the first step (...) of causal inference, where the features employed in the first step are exogenous to the case. Machine learning thus offers an approach to assess bias in the law and evaluate theories about the potential consequences of legal change. (shrink)

A major challenge for Dual Process Theories of reasoning is to predict the circumstances under which intuitive answers reached on the basis of Type 1 processing are kept or discarded in favour of analytic, Type 2 processing (Thompson 2009 ). We propose that a key determinant of the probability that Type 2 processes intervene is the affective response that accompanies Type 1 processing. This affective response arises from the fluency with which the initial answer is produced, such that fluently produced (...) answers give rise to a strong feeling of rightness. This feeling of rightness, in turn, determines the extent and probability with which Type 2 processes will be engaged. Because many of the intuitions produced by Type 1 processes are fluent, it is common for them to be accompanied by a strong sense of rightness. However, because fluency is poorly calibrated to objective difficulty, confidently held intuitions may form the basis of poor quality decisions. (shrink)

Kinetic demixing in quaternary mixed oxides has not been investigated previously, either theoretically or experimentally. In this theoretical study, we derive simple and exact analytical expressions that describe the steady-state cation concentration profiles resulting from kinetic demixing in mixed oxides of the O type. The concentration profiles are expressed in terms of cation-vacancy exchange frequency ratios. We assume a random distribution of cations and make use of the Moleko-Allnatt exact sum-rule expression relating the phenomenological coefficients in the ternary random alloy (...) to the vacancy mechanism operative. We employ Monte Carlo simulation of kinetic demixing to verify the result of the analysis. We discuss how kinetic demixing profiles can be processed to obtain atom-vacancy exchange frequency ratios. We also discuss how atom-vacancy exchange frequencies themselves might be obtained from available diffusivities in the quaternary oxide. (shrink)

The Recursive Bayesian Net (RBN) formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in particular (...) how a simple two-level RBN can be used to model a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell's mechanism for apoptosis. (shrink)

Lakatos’s approach to prediction and novel facts is of considerable interest. Prediction appears in his conception in at least three different levels: a) as an important aim of the research programs; b) as a procedure -a key method- for increasing our scientific knowledge both theoretically and empirically; and c) as the way to assess the scientific character of knowledge claims -means for evaluating results-. At all these levels he envisions a close connection between prediction and novel facts. The paper has (...) four aims. First, to examine his concept of “prediction” in Lakatos’s MSRP, taking into account different aspects. Second, to clarify the notion of “novel facts”, which requires the consideration of the various ways in which new facts can be understood. Third, to examine the prediction of novel facts as criterion of appraisal. Fourth, to explore Lakatos’s approach in connection with the field of economics, in order to shed new light on issues that have been discussed in recent years. (shrink)

The aim of this article is to provide a way of resolving the apparent dilemma between our requirement as agents that actions should be free and our demand as spectators that all events should be predictable and explicable on the basis of antecedent conditions. I hope to show that what has often been incorrectly regarded as a logical incompatibility between freedom and determinism is, in fact, a disparity but not an over-all contradiction between the viewpoint of an agent and that (...) of a spectator. While it is logically impossible for a person to deliberate about his conduct in a given matter from the standpoint of an agent and also predict it as a spectator, this is the only logical incompatibility between these positions, and it does not preclude the two points of view from being equally legitimate ways of viewing action. Perhaps it has sometimes been a vague recognition of the fact that one logically cannot both deliberate upon and predict one’s own conduct in a certain matter that has led some philosophers to conclude erroneously that choice on the part of an agent is inconsistent with prediction or explanation of his decision on the part of any spectator. This unwarranted conclusion is equivalent to denying that conduct can be regarded both from the standpoint of the agent and that of the spectator. (shrink)

Belief in astrology remains strong even today, and one of the explanations why some people endorse paranormal explanations is the individual differences in analytical thinking. Therefore, the main aim of this paper was to determine the effects of priming an analytical or intuitive thinking style on the credulity of participants. In two experiments (N= 965), analytic thinking was induced and the source of fake profile (astrological reading vs. psychological testing) was manipulated and participants’ prior paranormal beliefs, anomalous explanation, cognitive reflection, (...) and depression were measured. Although analytic thinking was proved to be hard to induce experimentally, the results showed that analytic thinking predicts credulity and belief in the paranormal was linked with experiencing more anomalous experiences and more paranormal explanations. The more people were able to think analytically, the less credulous they were as reflected in the lower acceptance of fake profile as accurate. (shrink)

Prediction is an important aspect of scientific practice, because it helps us to confirm theories and effectively intervene on the systems we are investigating. In ecology, prediction is a controversial topic: even though the number of papers focusing on prediction is constantly increasing, many ecologists believe that the quality of ecological predictions is unacceptably low, in the sense that they are not sufficiently accurate sufficiently often. Moreover, ecologists disagree on how predictions can be improved. On one side are the ‘theory-driven’ (...) ecologists, those who believe that ecology lacks a sufficiently strong theoretical framework. For them, more general theories will yield more accurate predictions. On the other are the ‘applied’ ecologists, whose research is focused on effective interventions on ecological systems. For them, deeper knowledge of the system in question is more important than background theory. The aim of this paper is to provide a philosophical examination of both sides of the debate: as there are strengths and weaknesses in both approaches to prediction, a pluralistic approach is best for the future of predictive ecology. (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)

In the present study, we have demonstrated hysteresis phenomena in the excitability of single, enzymatically dissociated guinea pig ventricular myocytes. Membrane potentials were recorded with patch pipettes in the whole-cell current clamp configuration. Repetitive stimulation with depolarizing current pulses of constant cycle length and duration but varying strength led to predictable excitation (1:l) and non-excitation (1:0) patterns depending on current strength. In addition, transition between patterns depended on the direction of current intensity change and stable hysteresis loops were obtained in (...) stimulus:response pattern vs. current intensity plots in 14 cells. Increase of pulse duration and decrease of stimulation rate contributed to a reduction in hysteresis loop areas. Changes in amplitude and shape of the subthreshold responses during the transitions from one stable pattern to the other, suggested that activity led to an increase in membrane resistance, particularly in the voltage domain between resting potential, and threshold. Therefore, we modelled the dynamic behaviour of the single cells as a function of diastolic membrane resistance, using previously published analytical solutions. Numerical iteration of the analytical model equations closely reproduced the experimental hysteresis loops in both qualitative and quantitative ways. In particular, the effect of stimulation frequency on the model was similar to the experimental findings. The overall study suggests that the excitability pattern of guinea pig ventricular myocytes accounts for hysteresis and bistabilities when current intensity is allowed to fluctuate around threshold levels. (shrink)

Basic characteristic of Islamic heritage law, principally it has accepted the two-to-one ratio between the male and the female children/siblings in division of heritage. In Islamic inheritance law, the main/basic reason why the share of the male is twice the share of the female is no “value” judgments given to female/women in creation and gender in Islam, on the contrary, are real realities related with the roles and financial obligations that man and woman have undertaken, in other words, related with (...) “socio-economic structure/fact” in the family and society structure foreseen by Islam. As a matter of fact, “need principle” is based on in division and succession of heritageand a fair arrangement has been made in accordance with the rights and responsibilities of the husband and wife in Islamic Law. In some classical tafsīr books, the concept of “degree” in the verse “... Men have a degree (right) over women” (Al-Baqara 2/228) mentioning the mutual rights and responsibilities of women and men; and the expression of “lil al-dhakari mithlu haẓẓ al-unthayain” in the verse –the inheritance of man is the share of two women– (Al-Nisā 4/11) mentioning the inheritance shares of boys and girls is interpreted against the woman by disregarding the intended purpose and socio-economic contexts of these verses. As a result of this interpretation, the share of men in inheritance is twice the share of women in Islamic law is ontologically (existential/creation) based on a justification that “man is superior to woman”. In this article/study, an analyticallook atthe interpretations in some classical tafsīr books on the axis of “daraja/degree” and “lil al-dhakari mithlu haẓẓ al-unthayain” that today sheds light on the sociological-historical background of depriving the daughter from the heritage will be made. Summary: Just as there is no way to determine a person’s sex, it is not either possible by reason to have such an opportunity. - With the possibility of medical intervention nowadays - sex is determined by the discretion of the Supreme Creator rather than will. Indeed, it is mentioned in the Qur’ān: To Allah belongs the dominion of the heavens and the earth; He creates what he wills. He gives to whom He wills female [children], and He gives to whom He wills males (Al-Shūrā 42/49.)In addition to human biological sex, there is also social gender. Indeed, the term “sex” refers to being biologically female or male, while the term "gender" refers to the social and cultural identity of a woman or man, or the social roles that occur in the historical process.Accordingly, while it is not possible to determine biological sex (in normal circumstances in advance), determining gender is shaped by the cultural will of individuals and societies. As a matter of fact, gender is shaped according to the religions, customs and cultures of the societies and it shows differences according to time, culture and family structure. In this context, in the pre-Islamic Arab society, the gender of the girl or the woman was shaped by the custom of the ritual and customs. Indeed, it is a known fact that during the period of Jahiliyyah, in terms of social gender, the girl/woman has been deprived of many social and economic rights, especially heritage. The Qur’ān has brought the girls who, in the period of Jahiliyyah, were oppressed in terms of gender, deprived of many social and economical rights, treated as second class human, embarrassed of themselves and buried alive, to the same position as man. In this context, as it is in every field in the direction of social structure and social conditions of that day, also in the field of inheritance law, a number of regulations were made in the Qur’ān and the Sunnah being the main sources of Islam. The divisions of the inheritance were connected with religious and legal rules and the shares of the inheritance of the sons and daughters were determined by naṣṣ (verses and hadiths).However, in Islamic inheritance law, as a requirement of the structure of family and society accepted by Islam, in principle, “two-to-one” measures have been adopted between male and female children. As a matter of fact, in this aspect, it is mentioned in the Qur’ān: Allah instructs you concerning your children: for the male, what is equal to the share of two females (Al-Nisā 4/11.)On one hand, the principle that Islamic law brings between boys and girls; Seems to be an inequality in terms of the arrangement in which "the inheritance share of the male child is twice the share of the female child", while on the other hand, within the border of in the family foreseen by Islam, this regulation has not been seen as an injustice and inequity by Muslim societies, because in Islamic family law, a man is obliged to ensure the livelihood of the family after marriage. He is also obliged to give his wife her mahr when marrying.In Islamic inheritance law, “necessity principle” is taken as the basis of responsibility that women and man have undertaken in family and society. Therefore, even though giving nothing at all to those who are not in need and giving less to those who are in less need, giving too much to those who are in much need might seem contrary to the principle of equality, it is a necessity of the principle of justice and fairness. As a matter of fact, while "law equality, necessity in sharing" principle, law is arranged according to people's qualifications, goods and wealth sharing is divided according to the needs of people. In this context, there has been a fair division in Islamic heritage law based on the necessity, (distributive) justice and fairness principle. Indeed, the French philosopher Roger Garaudy (1913-2012), who chose /converted to Islam, evaluates the following about the proportion of male child in the Qur'an to that of female child: “When we consider that in the Arab society all the obligations of the family and of the care of the parents and of all the things that we call ‘social security’ today are put on the shoulders of the husband, the hereditary male child's share must be twice as high as the female child’s is”.As Garaudy argues, the difference in the inheritance of women and men in Islamic inheritance law is not a legal discrimination/inequality, but a form of divisiveness stemming from a need based on the role and responsibility that women and men have undertaken in the family and society. Therefore, giving nothing to those who need nothing, giving little to those who need little, and giving a lot to those who need a lot,even though may seem contradictious to the principle of equality, it becomes a necessity of equity and (distributive) justice principle. In this case, in Islamic inheritance law, the basic reason why the share of the male child is twice the share of the female child, is social and economic reasons and it is possible to rank them as follows:1) According to Islamic law, women are not obliged to make their own economic livelihoods. The woman’s economic responsibility belongs to her father or brothers before marriage, and then to her husband after marriage. 2) When a woman is married she is not responsible for herself or other family members’ livelihood. The male is obliged to make a living for himself, his wife and his children.3) While married, the male is obliged to give the wife mahr. The woman has no such responsibility.As it is understood from the above explanations, in Islamic inheritance law, the basic reason why the share of the male child is twice the share of the female child is not about the ontologically “value” based on creation and sex given to the woman (girl child) in Islam. On the contrary, it is the real facts concerning the family and society structure that Islam predicts, the roles and financial obligations that man and woman have undertaken, namely “socio-economic structure/fact”.In some commentaries in classical commentary books, the rights and responsibilities of women and men are referred to, like: the word “degree” mentioned in: …but the men have a degree over them [in responsibility and authority (Al-Baqara 2/228), and the talk about the inheritance shares of boys and girls in: for the male, what is equal to the share of two females (Al-Nisā 4/11). Eventually, the concepts “lil al-dhakari mithlu haẓẓ al-unthayain” have been associated with the gender of the woman/girl child ontologically (based on social fact) by ignoring the referent purpose and socio-economic contexts of these verses. As a result of these interpretations, it was desired that the Islamic law principle of inheritance share of male child being twice the share of female child, ontologically, should be based on a justification that “man is superior to woman”.In this study, some of the era’s dominant culture classical interpretations grounding women's inheritances share on her gender and based on the axis of the concepts of "degree" and “lil al-dhakari mithlu haẓẓ al-unthayain” in the related verses of the Qur'ān will be elaborated. (shrink)

The Analytic/Synthetic distinction did not originate in Kant, but in Port-Royal's logical theory. The key for the doctrine is the explicite recognition of two different kinds of relative clauses, e.g. explicative and determinative. In the middle eighteenth century the distinction becomes a topic within the grammars. Although we can find by grammarians different criteria for the distinction, these criteria (for which we can find medieval sources) are for the main predictable from the original theory of ideas, which was presented in (...) Port-Royal's logical writings. The topic of the two relative clauses (somewhat broader than the analytic/synthetic distinction) can be used to give empirical criteria for analyticity and also for revisiting Quine's criticism of the topic. Analyticity yet appears as a master piece of classical linguistic philosophy and not as being the empty dogma of modern empiricism. (shrink)

For the past two years, I have trained teachers in Dr. Matthew Lipman's Philosophy for Children program. During 1979-80, I worked with a group of ten suburban elementary school teachers, half of whom were teaching the gifted and talented; this year my class is composed of twenty elementary school teachers working in the regular classroom in an urban setting. A very brief comparison, based upon my observations, of how the program works with the suburban gifted and with inner-city students who (...) are frequently weak in basic skills reveals both predictable differences and surprising similarities. (shrink)

The article focuses on exploring the directions for implementing innovative analytical-statistical technologies as a tool for monitoring and detecting corruption in the state. To achieve this goal, the author clarifies the content of key concepts, defines the essence of innovative analytical-statistical technologies, and analyzes the applications of these technologies as elements of the state’s anti-corruption policy. It is determined that modern analytical-statistical technologies are integral to information technologies, which have emerged as a separate branch of production known as the information (...) industry. Information technologies, including analytical-statistical ones, are realized through information systems, which combine technical tools (computers, communication devices and channels, peripherals, input/output devices, etc.) with software applications that facilitate the functioning of the technical components and analytical aspects, including the mathematical component (statistics). The use of analytical-statistical technologies as a tool to counter corruption at the state level is driven by the specificity of the corruption identification process. The application of relevant technologies is possible when perceiving corruption as a form of fraud. Therefore, the search for corruption in modern society requires a comprehensive approach, utilizing mathematical, analytical, and psychophysical research methods. This approach enables not only the identification but also the prediction of probable instances of abuse. Five directions for implementing innovative analytical-statistical technologies in anti-corruption activities are identified: 1) automation of data collection and processing; 2) automation of communication and office processes; 3) automation of direct management processes; 4) automation of decision-making processes and development; 5) development of expert systems. It is noted that analytical-statistical technologies find the most implementation in four of the identified directions: data collection/processing, direct management, decision support, and expert support. (shrink)

The relationship between corporate social responsibility and corporate financial performance has long been a central and contentious debate in the literature. However, prior empirical studies provide indefinite conclusions. The purpose of this study is to review systematically and quantify the CSR–CFP link in a meta-analytic framework. Based on 119 effect sizes from 42 studies, this study estimates that the overall effect size of the CSR–CFP relationship is positive and significant, thus endorsing the argument that CSR does enhance financial performance. Furthermore, (...) this work sheds light on the causal relationship between CSR and CFP. Subsequent financial performance is associated with prior social responsibility, while the reverse direction is not supported. This finding supports the instrumental stakeholder theory. As predicted, the meta-analysis results indicate that the measurement strategies of the two key constructs of CSR and CFP explain some variations of the CSR–CFP relationship. Last, this study examines the moderating effect of the environmental context on the CSR–CFP link. This work proposes that CSR in the developed world, with a relatively mature institutional system and efficient market mechanism, will be more visible than CSR in the developing world. The results show that the CSR–CFP relationship is stronger for firms from advanced economies than for firms from developing economies. (shrink)

In this article, we show how it is possible to lawfully buy an election. The method we describe for buying an election is novel. The key things that make it possible to buy an election are the existence of public voter registration lists where one can see whether a given elector has voted in a particular election, and the existence of Big Data Analytics that with a high degree of accuracy can predict what a given elector will vote in (...) an upcoming election. Someone interested in buying an election can enter an employment contract with all, or some of, the opponent electors where these electors are paid to do a job that prevents them from voting. By purchasing access to the public voter registration lists, it is possible to verify ex-post whether the opponent electors that one has signed a contract with have abstained. In the last two sections of the article, we discuss several barriers that can undermine an attempt to buy an election in the manner we identify. (shrink)