Test of the analysis of competing hypotheses in legal decision‐making

The analysis of competing hypotheses (ACH) has been suggested to be a method that can protect against confirmation bias in the context of intelligence analysis. In the current study, we aimed to determine whether ACH could counter confirmation bias in the reasoning with evidence in the context of criminal law proceedings. Law students (N = 191) received information about the ACH method or general information about biases. They were given a case vignette with a main suspect and a list of 24 questions, 6 of which they could ask about the case. Half of the questions related to incriminating information, whereas the other half related to exonerating information. Contrary to our expectations, participants in both conditions favoured questions relating to exonerating information and rated the exonerating evidence as being more important for their decision. Despite the lack of bias observed, it seems participants failed to properly apply the ACH method.     

具身化空间四卡问题解决的内容效应

利用三个实验探讨了左右、前后(实验1,2)具身化空间四卡问题解决的内容效应,同时探讨了条件推理后件类型(二分变量与连续性变量)对具身化内容效应的影响(实验3)。结果发现:(1)三个实验均表现出在自我参照空间四卡问题解决中,肯定前件和否定后件同时被选择的比率(P-Q)显著高于在经典四卡问题或环境参照空间四卡问题中P-Q卡被选择的比率,从而表现出四卡问题解决存在具身化内容效应;(2)具身化内容效应仅限于后件类型是二分变量的四卡问题;(3)在三个实验中被试均表现出"证真偏向"。具身化空间四卡问题解决的内容效应支持了条件推理领域特异性理论。     

Rigorous results,cross-model justification,and the transfer of empirical warrant: the case of many-body models in physics

This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on to one another. Not only does this put constraints on the extent to which performance in specific empirical contexts may be regarded as the main touchstone of success in scientific modelling, it also allows for the transfer of warrant across different models. Mathematically rigorous results can thus come to be seen as not only strengthening the cohesion between scientific strategies of modelling and simulation, but also as offering new ways of indirect confirmation.     

Confirmation Ministry in the Crossfire of Tolerance and Fascism

This article discuses the vitality of confirmation ministry in India in the present social, economic, and political contexts. The article analyses how confirmation ministry in the Andhra Evangelical Lutheran Church contributes to Lutheran identity and leadership, dealing briefly with the theological impetus from Luther's Small Catechism and Luther's theology of sola fide and sola gratsia     

中国远程学习者学习风格理论模型与验证

为帮助中国远程学习者了解自身的学习风格,选择相应的学习策略,进而提高远程学习质量,根据学习风格的信息加工理论、Kolb的经验学习理论以及荣格的人格特征类型理论,从生理、社会、心理三个维度,构建了我国远程学习者学习风格的理论模型,通过编制量表和实际测量,对该模型进行验证分析和修订完善.结果表明,最初提出的理论模型假设得到验证,修订后的量表具有良好的效度和信度,可以用来测量我国远程学习者的学习风格.     

When good theories make bad predictions

Chaos-related obstructions to predictability have been used to challenge accounts of theory validation based on the agreement between theoretical predictions and experimental data (Rueger & Sharp, 1996. The British Journal for the Philosophy of Science, 47, 93–112; Koperski, 1998. Philosophy of Science, 40, 194–212). These challenges are incomplete in two respects: (a) they do not show that chaotic regimes are unpredictable in principle (i.e., with unbounded resources) and, as a result, that there is something conceptually wrong with idealized expectations of correct predictions from acceptable theories, and (b) they do not explore whether chaos-induced predictive failures of deterministic models can be remedied by stochastic modeling. In this paper we appeal to an asymptotic analysis of state space trajectories and their numerical approximations to show that chaotic regimes are deterministically unpredictable even with unbounded resources. Additionally, we explain why stochastic models of chaotic systems, while predictively successful in some cases, are in general predictively as limited as deterministic ones. We conclude by suggesting that the way in which scientists deal with such principled obstructions to predictability calls for a more comprehensive approach to theory validation, on which experimental testing is augmented by a multifaceted mathematical analysis of theoretical models, capable of identifying chaos-related predictive failures as due to principled limitations which the world itself imposes on any less-than-omniscient epistemic access to some natural systems. We give special thanks to two anonymous reviewers for their helpful comments that have substantially contributed to the final version of this paper     

The Logic of Theory Assessment

This paper starts by indicating the analysis of Hempel’s conditions of adequacy for any relation of confirmation (Hempel, 1945) as presented in Huber (submitted). There I argue contra Carnap (1962, Section 87) that Hempel felt the need for two concepts of confirmation: one aiming at plausible theories and another aiming at informative theories. However, he also realized that these two concepts are conflicting, and he gave up the concept of confirmation aiming at informative theories. The main part of the paper consists in working out the claim that one can have Hempel’s cake and eat it too — in the sense that there is a logic of theory assessment that takes into account both of the two conflicting aspects of plausibility and informativeness. According to the semantics of this logic, α is an acceptable theory for evidence β if and only if α is both sufficiently plausible given β and sufficiently informative about β. This is spelt out in terms of ranking functions (Spohn, 1988) and shown to represent the syntactically specified notion of an assessment relation. The paper then compares these acceptability relations to explanatory and confirmatory consequence relations (Flach, 2000) as well as to nonmonotonic consequence relations (Kraus et al., 1990). It concludes by relating the plausibility-informativeness approach to Carnap’s positive relevance account, thereby shedding new light on Carnap’s analysis as well as solving another problem of confirmation theory. A precursor of this paper has appeared as “The Logic of Confirmation and Theory Assessment” in L. Běhounek & M. Bílková (eds.), The Logica Yearbook 2004, Prague: Filosofia, 2005, 161–176.     

Refining the blank line-up procedure: How should we instruct eyewitnesses?

Presenting a blank line-up—containing only fillers—to witnesses prior to showing a real line-up might be useful for screening out those who pick from the blank line-up as unreliable witnesses. We show that the effectiveness of this procedure varies depending on instructions given to witnesses. Participants (N = 462) viewed a simulated crime and attempted to identify the perpetrator from a line-up approximately 1 week later. Rejecting a blank line-up was associated with greater identification accuracy and greater diagnosticity of suspect identifications, but only when witnesses were instructed prior to the blank line-up that they would view a series of line-ups; the procedure was ineffective for screening when witnesses were advised they would view two line-ups or received no instruction. These results highlight the importance of instructions used in the blank line-up procedure, and the need for better understanding of how to interpret choosing patterns in this paradigm.     

Recommendations for Increasing Replicability in Psychology

Replicability of findings is at the heart of any empirical science. The aim of this article is to move the current replicability debate in psychology towards concrete recommendations for improvement. We focus on research practices but also offer guidelines for reviewers, editors, journal management, teachers, granting institutions, and university promotion committees, highlighting some of the emerging and existing practical solutions that can facilitate implementation of these recommendations. The challenges for improving replicability in psychological science are systemic. Improvement can occur only if changes are made at many levels of practice, evaluation, and reward. Copyright © 2013 John Wiley & Sons, Ltd.     

Why experiments matter*

Experimentation is traditionally considered a privileged means of confirmation. However, why and how experiments form a better confirmatory source relative to other strategies is unclear, and recent discussions have identified experiments with various modeling strategies on the one hand, and with ‘natural’ experiments on the other hand. We argue that experiments aiming to test theories are best understood as controlled investigations of specimens. ‘Control’ involves repeated, fine-grained causal manipulation of focal properties. This capacity generates rich knowledge of the object investigated. ‘Specimenhood’ involves possessing relevant properties given the investigative target and the hypothesis in question. Specimens are thus representative members of a class of systems, to which a hypothesis refers. It is in virtue of both control and specimenhood that experiments provide powerful confirmatory evidence. This explains the distinctive power of experiments: although modelers exert extensive control, they do not exert this control over specimens; although natural experiments utilize specimens, control is diminished.