Paranormal belief and errors of probabilistic reasoning: The role of constituent conditional relatedness in believers' susceptibility to the conjunction fallacy

The present study examines the extent to which stronger belief in either extrasensory perception, psychokinesis or life-after-death is associated with a proneness to making conjunction errors (CEs). One hundred and sixty members of the UK public read eight hypothetical scenarios and for each estimated the likelihood that two constituent events alone plus their conjunction would occur. The impact of paranormal belief plus constituents’ conditional relatedness type, estimates of the subjectively less likely and more likely constituents plus relevant interaction terms tested via three Generalized Linear Mixed Models. General qualification levels were controlled for. As expected, stronger PK beliefs and depiction of a positively conditionally related (verses conditionally unrelated) constituent pairs predicted higher CE generation. ESP and LAD beliefs had no impact with, surprisingly, higher estimates of the less likely constituent predicting fewer - not more - CEs. Theoretical implications, methodological issues and ideas for future research are discussed.     

From Assigning to Designing Technological Agency

In What Things Do, Verbeek (What things do: philosophical reflections on technology, agency and design. Penn State University Press, University Park, 2005a) develops a vocabulary for understanding the social role of technological artifacts in our culture and in our daily lives. He understands this role in terms of the technological mediation of human behavior and perception. To explain mediation, he levels out the modernist separation of subjects and objects by decreasing the autonomy of humans and increasing the activity of things. His approach consists primarily within a clever integration of the theories of Latour and Ihde, which provides a comprehensive understanding of the social role of technological artifacts. Despite the fact that Verbeek’s book is carefully thought out and already quite influential in the field of philosophy of technology, his approach raises some conceptual and pragmatic questions. The conceptual questions concern (a) the precise meaning of the concept of mediation and the possibility of distinguishing between different forms of mediation, and (b) the differences and similarities between human and technological agency and intentionality. The pragmatic questions concern the application of his theory to the realm of engineering ethics. Particularly pressing is the question of how to assign (moral) responsibility to humans when technological artifacts are mediating the outcomes of human actions. With this article, I will raise these issues, and look forward to Verbeek’s reply.

From mere coincidences to meaningful discoveries

People's reactions to coincidences are often cited as an illustration of the irrationality of human reasoning about chance. We argue that coincidences may be better understood in terms of rational statistical inference, based on their functional role in processes of causal discovery and theory revision. We present a formal definition of coincidences in the context of a Bayesian framework for causal induction: a coincidence is an event that provides support for an alternative to a currently favored causal theory, but not necessarily enough support to accept that alternative in light of its low prior probability. We test the qualitative and quantitative predictions of this account through a series of experiments that examine the transition from coincidence to evidence, the correspondence between the strength of coincidences and the statistical support for causal structure, and the relationship between causes and coincidences. Our results indicate that people can accurately assess the strength of coincidences, suggesting that irrational conclusions drawn from coincidences are the consequence of overestimation of the plausibility of novel causal forces. We discuss the implications of our account for understanding the role of coincidences in theory change.     

Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma–Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information‐theoretic formalism.     

From Bayesian epistemology to inductive logic

Inductive logic admits a variety of semantics (Haenni et al. (2011) [7, Part 1]). This paper develops semantics based on the norms of Bayesian epistemology (Williamson, 2010 [16, Chapter 7]). Section 1 introduces the semantics and then, in Section 2, the paper explores methods for drawing inferences in the resulting logic and compares the methods of this paper with the methods of Barnett and Paris (2008) [2]. Section 3 then evaluates this Bayesian inductive logic in the light of four traditional critiques of inductive logic, arguing (i) that it is language independent in a key sense, (ii) that it admits connections with the Principle of Indifference but these connections do not lead to paradox, (iii) that it can capture the phenomenon of learning from experience, and (iv) that while the logic advocates scepticism with regard to some universal hypotheses, such scepticism is not problematic from the point of view of scientific theorising.     

The effects of endowment on the demand for probabilistic information

Research shows that individuals are ambiguity averse: they choose unambiguous over equivalent ambiguous prospects and price them higher (either as buyers or sellers). Moreover, it is often assumed that ambiguity averse individuals are willing to pay an ambiguity premium for information that reduces ambiguity [Camerer, C. F., & Weber, M. (1992). Recent developments in modeling preferences: Uncertainty and ambiguity. Journal of Risk and Uncertainty, 5(4), 325–370]. However, when people are asked to exchange an ambiguous alternative in their possession for an equivalent unambiguous one, they prefer to retain the former [Roca, M., Hogarth, R. M., & Maule, A. J. (2006). Ambiguity seeking as a result of the status quo bias. Journal of Risk and Uncertainty, 32(3), 175–194]. We present three experiments investigating the economic effects of endowment on attitudes towards ambiguity and the ambiguity premium. The experiments, based on a [Becker, G., DeGroot, M., & Marschak, J. (1964). Measuring utility by a single-response sequential method. Science, 9, 3] procedure, show that the value attributed to ambiguity reducing information is substantially affected by the status quo of the individual.     

The impact of self‐confidence on the compromise effect

This research reports an investigation into whether the personality aspect of self‐confidence affects the compromise effect. We hypothesize that highly self‐confident people have greater certainty in making decisions and are more attracted to risk‐taking, which makes them less likely to choose the safe or middle option in a large choice set. The three studies involved are conducted using between‐ and within‐subjects experimental designs. Various product categories are used to generalize the findings. Study 1 looks at purchasing decisions and utilizes three scales of self‐confidence, risk preference, and uncertainty; it demonstrates that consumers with high self‐confidence are less likely to choose a compromise option due to high certainty in their decision‐making. Study 2 discovers that people with low self‐confidence are more likely to choose the middle option in a risky condition than in a nonrisky condition. Study 3 decomposes self‐confidence into general and specific self‐confidence, and reveals that people with low general self‐confidence and low specific self‐confidence are more likely to choose the middle option.     

Ethics of Risk Analysis and Regulatory Review: From Bio- to Nanotechnology

Risk analysis and regulatory systems are usually evaluated according to utilitarian frameworks, as they are viewed to operate “objectively” by considering the health, environmental, and economic impacts of technological applications. Yet, the estimation of impacts during risk analysis and the decisions in regulatory review are affected by value choices of actors and stakeholders; attention to principles such as autonomy, justice, and integrity; and power relationships. In this article, case studies of biotechnology are used to illustrate how non-utilitarian principles are prominent in risk analysis and regulatory review and to argue that these relationships should be carefully considered as we consider nanotechnology oversight systems for its products. We argue that there are not distinct separations between “science-based” review systems, in which evaluations of the consequences of technological products are primarily considered, and principles of integrity, justice, non-maleficence, and autonomy. It should further be expected that, given research into fair treatment during decision-making processes, attention to ethics will affect how citizens assess emerging technologies. Finally, a more holistic approach for evaluating oversight systems for the products of nanotechnology is suggested, one which does not draw a sharp distinction between risk analysis, regulation, and respect for non-utilitarian values.

Religious versus reflective priming and susceptibility to the conjunction fallacy

The effect of religious priming has been studied in relation to a number of variables, most extensively with prosocial behavior. The effects of priming on cognitive domains, however, are relatively understudied. The present study examined the effects of religious priming, compared with reflective and neutral priming, on the conjunction fallacy. Participants were randomly assigned to 1 of the 3 priming conditions. Priming was presented through the scrambled sentence task in which participants were required to rearrange words of a religious (e.g., pray), reflective (e.g., reason), or neutral (e.g., paper) content. The conjunction fallacy was measured by a task containing 1 problem. Results indicated that those undergoing the religious prime were significantly more likely to commit the conjunction fallacy compared with those in the reflective priming group. Situations in which reasoning is integral may benefit from knowing the immediate effects of religious versus reflective stimuli in the environment.     

Candidate Vulnerability and Exposure to Counterattitudinal Information: Evidence From Two U.S. Presidential Elections

Politically motivated selective exposure has traditionally been understood through the lens of long‐standing attitudes and beliefs, but the role of environment in shaping information exposure practices merits further consideration. Citizens might respond to the political environment in their information‐seeking behavior for numerous reasons. Citizens who believe their position is politically vulnerable have specific cognitive and affective needs that may make them uniquely attuned to counterattitudinal information. In the context of a presidential election, this means that as the defeat of a supported candidate appears more likely, attention to counterattitudinal content will increase. Data collected in the 2008 and 2012 U.S. Presidential elections support this prediction, although this relationship was observed primarily among supporters of the Republican candidate in both elections.     

An overview of algorithmic approaches to compute optimum entropy distributions in the expert system shell MECore (extended version)

The expert system shell MECore provides a series of knowledge management operations to define probabilistic knowledge bases and to reason under uncertainty. To provide a reference work for MECore algorithmics, we bring together results from different sources that have been applied in MECore and explain their intuitive ideas. Additionally, we report on our ongoing work regarding further development of MECore's algorithms to compute optimum entropy distributions and provide some empirical results. Altogether this paper explains the intuition of important theoretical results and their practical implications, compares old and new algorithmic approaches and points out their benefits as well as possible limitations and pitfalls.     

When fairness neither satisfies nor motivates: The role of risk aversion and uncertainty reduction in attenuating and reversing the fair process effect

It is widely acknowledged that procedural justice has many positive effects. However, some evidence suggests that procedural justice may not always have positive effects and may even have negative effects. We present three studies that vary in method and participant populations, including an archival study, a field study, and an experiment, using data provided by the general American population, Indian software engineers, and undergraduate students in the US. We demonstrate that key work-related variables such as people’s job satisfaction and performance depend on procedural justice, perceived uncertainty, and risk aversion such that risk seeking people react less positively and at times negatively to the same fair procedures that appeal to risk averse people. Our results suggest that one possible reason for these effects is that being treated fairly reduces people’s perception of uncertainty in the environment and while risk averse people find low uncertainty desirable and react positively to it, risk seeking people do not. We discuss the implications of our findings for theories of procedural justice including the uncertainty management model of fairness, the fair process effect, and fairness heuristic theory.     

From exemplar to grammar: a probabilistic analogy-based model of language learning

While rules and exemplars are usually viewed as opposites, this paper argues that they form end points of the same distribution. By representing both rules and exemplars as (partial) trees, we can take into account the fluid middle ground between the two extremes. This insight is the starting point for a new theory of language learning that is based on the following idea: If a language learner does not know which phrase-structure trees should be assigned to initial sentences, s/he allows (implicitly) for all possible trees and lets linguistic experience decide which is the "best" tree for each sentence. The best tree is obtained by maximizing "structural analogy" between a sentence and previous sentences, which is formalized by the most probable shortest combination of subtrees from all trees of previous sentences. Corpus-based experiments with this model on the Penn Treebank and the Childes database indicate that it can learn both exemplar-based and rule-based aspects of language, ranging from phrasal verbs to auxiliary fronting. By having learned the syntactic structures of sentences, we have also learned the grammar implicit in these structures, which can in turn be used to produce new sentences. We show that our model mimicks children's language development from item-based constructions to abstract constructions, and that the model can simulate some of the errors made by children in producing complex questions.     

From riskier to safer driving decisions: The role of feedback and the experiential automatic processing system

Decision making in risky driving contexts is mainly guided by automatic processes. This requires the previous learning of cognitive rules and heuristics. The acquisition of safer cognitive heuristics depends on previous experience and adequate feedback to our responses. The first aim of this research was to analyze the effect of negative feedback on risk evaluation and decision processes in dangerous and harmless driving contexts. The second aim was to demonstrate the influence of prior experience upon the process of decision-making and feedback, comparing individuals with and without driving experience. One hundred and three participants (with and without driving license) were required to evaluate a set of 120 driving images with respect to the risk level of the situations and decide whether to brake or not. Half of the participants received negative feedback. The results showed that decisions were faster and more accurate than evaluations, and both were improved by the effect of feedback and previous experience in risk situations. However, the same feedback resulted in inaccurate risk evaluations and decisions in harmless situations. The cognitive processes underlying these effects point to a response bias rather than to discriminative factors. These results clarify the effect of negative feedback and previous experience on different phases of the decision-making process, showing the importance of these factors for the automatic processes and cognitive heuristics implied in driving. Our findings have potentially important applied value in the promotion of safe driving practices.     

人格测量：从累积式模型到展开式模型

当前大多数人格测量都采用的是累积式反应模型方法,该模型假设被试在测验上的得分随其能力或特质提高而增加,但是随着人格测量技术的不断发展,这一模型的实施效果遭到了质疑,研究者们开始关注展开式模型,该模型认为被试的反应取决于被试能力和项目阈值的匹配程度,当被试能力与项目阈值完全匹配时,被试做出肯定回答的概率达到最高点,称之为“理想点”,展开式模型的目的就是找到被试的理想点,从而寻找其真正的态度强度或人格特质水平。GGUM作为一种比较成熟的展开式模型,已经开始应用于人格测量的各个领域,但仍需要进行大规模的试测,在评估和预测效度方面积累经验,建立业界认可的心理测量学标准,不断探讨和开发相应的心理测量理论和简便易行的统计程序。     

Ethics Consultation in Pediatrics: Long-Term Experience From a Pediatric Oncology Center

There is little information about the content of ethics consultations (EC) in pediatrics. We sought to describe the reasons for consultation and ethical principles addressed during EC in pediatrics through retrospective review and directed content analysis of EC records (2000–2011) at St. Jude Children's Research Hospital. Patient-based EC were highly complex and often involved evaluation of parental decision making, particularly consideration of the risks and benefits of a proposed medical intervention, and the physician's fiduciary responsibility to the patient. Nonpatient consultations provided guidance in the development of institutional policies that would broadly affect patients and families. This is one of the few existing reviews of the content of pediatric EC and indicates that the distribution of ethical issues and reasons for moral distress are different than with adults. Pediatric EC often facilitates complex decision making among multiple stakeholders, and further prospective research is needed on the role of ethics consultation in pediatrics.     

From Gibson and Crooks to Damasio: The role of psychology in the development of driver behaviour models

This article presents a brief history and perspective of behavioural model development in traffic psychology. As one specific example of a key behavioural model, Gibson and Crooks (1938), in their classic field theoretical study, offered the first scientific attempt to deal with the issue of compensation. Two central theoretical concepts were developed: “Field of safe travel” and “Minimum stopping zone”. The interplay between the two was used to describe and explain risk compensation and illustrated by observing the impact of brakes on driver behaviour: Better brakes could make the field of safe travel – i.e. the distance to the car in front – shorter. Nearly 50 years later, the launch of Wilde’s Risk Homeostasis Theory (RHT) gave rise to a profound debate about risk homeostasis and risk compensation. The core issue in the debate was Wilde’s strict assertion that all individuals, not only car-drivers, carry an inherent target level of risk that they are seeking to maintain or restore. Gibson and Crooks fell well within psychological theories of the time, while Wilde’s RHT emerged more from control theory and economic utility theory than from psychology. In the 1990s neuroscience emerges, especially by Damasio who introduces a paradigm that has proven fruitful as a framework of more recent driver behaviour models. But neuroscience also had its forerunner in Taylor’s proposal that driver behaviour is governed by a constancy in Galvanic Skin Response (GSR) which makes driving a self-paced task aiming at keeping the GSR at a constant level. Näätänen and Summala’s integrated Taylor in their “Zero-risk model” which has persisted and still prevails as a solid and well accepted model. Psychological learning theory has, however, rarely been adequately dealt with which is quite odd given the prevalence of speeding and risk compensation which cannot escape explanations based on operant conditioning. The paper discusses the emerging role of psychology and psychological concepts that has been proposed and evolved through the development of driver behaviour models since Gibson and Crooks’ study of 1938. The views presented are subjective, they do not represent any attempt to describe the objective reality of the time.     

Special random numbers: Beyond the illusion of control

Previous research has shown that gamblers prefer numbers they choose themselves because this choice allows them to feel more in control of the (random) outcome. We identify other conditions under which people find numbers “special” (i.e., worthy of betting more on than other numbers). By manipulating gambling task type and assigning participants a number by an endogenous system outside their own control (as is done in numerology, astrology, and other paranormal systems), we find that indeed people prefer to bet on numbers derived from particular special systems. The mechanism underlying this preference is enjoyment with the task—not control. Further, the enjoyment associated with this “specialness” is related to the prevalence of certain types of numbers (i.e., numbers based on dates and names) in the fortune-telling world and not to other factors such as individuality or even belief in the associated system. We replicate these findings using actual money and show that this prevalence-to-enjoyment link already exists in memory for dates and names and is activated and strengthened by priming the fortune-telling systems relevant to those special random numbers. Finally, we present a model of special random numbers that integrates our findings with other determinants of valuation such as regret and subjective probability. Our results expand the realm of special random numbers beyond control. Our enjoyment model has implications not only for understanding gambling, but also for understanding how reasoning under uncertainty is influenced by little-understood phenomena (such as fortune-telling systems) without affecting subjective probability or actual beliefs.     

从冠心病主要危险因素的流行特点谈医学模式的转变

随着人民生活水平的提高,冠心病的发病率呈逐年上升趋势,不仅造成个人很高的致残率或致死率,而且给家庭和社会带来沉重的经济负担,冠心病已成为当前一个重要的公共卫生问题。而冠心病是一个多病因疾病,是可防可控的。充分了解冠心病危险因素的流行现状及危害,转变理念,着眼预防,逐步改变目前"重治轻防"的医学模式,是我们心血管医生神圣的使命。     

On the assessment of procedural knowledge: From problem spaces to knowledge spaces

By generalizing and completing the work initiated by Stefanutti and Albert (2003, Journal of Universal Computer Science, 9, 1455), this article provides the mathematical foundations of a theoretical approach whose primary goal is to construct a bridge between problem solving, as initially conceived by Newell and Simon (1972, Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.), and knowledge assessment (Doignon and Falmagne, 1985, International Journal of Man-Machine Studies, 23, 175; Doignon and Falmagne, 1999, Knowledge spaces. Berlin, Germany: Springer-Verlag.; Falmagne et al., 2013, Knowledge spaces: Applications in education. New York, NY: Springer-Verlag; Falmagne and Doignon, 2011, Learning spaces: Interdisciplinary applied mathematics. Berlin, Germany: Springer-Verlag.). It is shown that the collection of all possible knowledge states for a given problem space is a learning space. An algorithm for deriving a learning space from a problem space is illustrated. As an example, the algorithm is used to derive the learning space of a neuropsychological test whose problem space is well known: the Tower of London (TOL; Shallice, 1982, Philosophical Transactions of the Royal Society of London B: Biological Sciences, 298, 199). The derived learning space could then be used for adaptively assessing individual planning skills with the TOL.