Explanation,updating, and accuracy

There is evidence that people update their credences partly on the basis of explanatory considerations. Philosophers have recently argued that to minimise the inaccuracy of their credences, people's updates also ought to be partly based on such considerations. However, there are many ways in which explanatory considerations can factor into updating, not all of which minimise inaccuracy. It is an open question whether in their updating, people take explanatory considerations into account in a way that philosophers would deem recommendable. To address this question, we re-analyse data from an experiment reported in Douven and Schupbach, “The role of explanatory considerations in updating” (Cognition, 2015).     

材料模式与认知负荷对小学生类比学习的影响

探讨学习材料不同模式和学习过程不同的认知负荷对小学生类比推理学习迁移的影响.包括两个分实验.实验1探讨学习材料的不同组织模式对小学生类比推理学习迁移的影响,两组小学生分别学习模式化与非模式化的材料,然后完成迁移程度远近不同的四类测题.结果表明,非模式化条件下完成远迁移题目的成绩显著优于模式化条件下的成绩.实验2探讨小学生在不同认知负荷条件下类比推理学习的迁移效果,两组小学生分别在高认知负荷与低认知负荷情况下学习类比推理的材料,然后完成上述四类测题.结果表明,高认知负荷条件下完成远迁移题目的成绩显著优于低认知负荷条件下的成绩.本实验结果表明,对于小学生类比推理的学习来说,非模式化、高负荷的学习更有利于促进迁移,支持了积极反应理论.     

Mass Response to the Lewinsky Scandal: Motivated Reasoning or BayesianUpdating?

This study attempts to account for the vastly different trajectories taken by mass andelite opinion in the wake of the Lewinsky affair. Data from a panel study, collected before andjust after the scandal broke, suggest that Clinton's prior popularity indelibly colored massresponse to the scandal, thereby constraining citizens' reactions. As would be predicted bytheories of "motivated reasoning," the influence of various considerations (like thecredibility and importance of the allegations) on reactions to the scandal was conditional uponprior affect for the president. Such findings are difficult to accommodate within the more rational"Bayesian updating" perspective. These data shed light on mass response to theLewinsky scandal in particular and citizen reaction to presidential behavior more generally, aswell as on the cognitive mechanisms that facilitate motivated reasoning in candidate evaluation.     

How do investors make predictions? Insights from analogical reasoning research

Previous work on investor decision making has focused almost exclusively on information specific to the company being judged. Consequently, every decision is viewed as a novel event, disconnected from the investor's existing knowledge. In this study, the analogical reasoning literature provides the theoretical support for arguing that investors frequently utilize existing knowledge as a basis for generating predictions about a company's future. The specific proposal is that investors transfer their existing knowledge via two different forms of analogical reasoning. The first, relational reasoning, is based primarily on structural correspondence between a novel company and an existing schema. The second, literal similarity reasoning, is based primarily on surface correspondence of a novel company and a previously encountered company. Our theoretical framework is tested in a study in which experienced investors predict the outcome of a novel company's strategy after reading about the experiences of other companies who implemented a similar strategy. The results are consistent with the occurrence of both relational and literal similarity reasoning, with relational reasoning emerging as the dominant approach to generating investors' predictions. Copyright © 2000 John Wiley & Sons, Ltd.     

Political Attitudes and the Processing of Misinformation Corrections

Misinformation often continues to influence people’s memory and inferential reasoning after it has been retracted; this is known as the continued influence effect (CIE). Previous research investigating the role of attitude‐based motivated reasoning in this context has found conflicting results: Some studies have found that worldview can have a strong impact on the magnitude of the CIE, such that retractions are less effective if the misinformation is congruent with a person’s relevant attitudes, in which case the retractions can even backfire. Other studies have failed to find evidence for an effect of attitudes on the processing of misinformation corrections. The present study used political misinformation—specifically fictional scenarios involving misconduct by politicians from left‐wing and right‐wing parties—and tested participants identifying with those political parties. Results showed that in this type of scenario, partisan attitudes have an impact on the processing of retractions, in particular (1) if the misinformation relates to a general assertion rather than just a specific singular event and (2) if the misinformation is congruent with a conservative partisanship.     

The effect of decision timing on the willingness to costly reward cooperation and punish noncooperation: Sanctioning the past,the present,or the future

Numerous studies have demonstrated that sanctions can promote cooperation. However, it is important to know not only that sanctions can work but also under what conditions people are actually willing to sanction cooperation positively (i.e., reward) or noncooperation negatively (i.e., punish). In this article, we demonstrate that people use sanctions less often and sanction more mildly when they decide about sanctioning before (instead of after) the occurrence of others' (non)cooperation (Experiments 1 and 2), regardless of whether they decide directly afterwards or after a time delay (Experiment 2). Moreover, we reveal that beforehand (as compared with afterwards) people have not yet formed clear sanctioning preferences (Experiment 3). These findings corroborate our reasoning that the decision environment beforehand induces nonconsequential reasoning and thereby hampers people's willingness to sanction. We discuss the theoretical, methodological, and practical implications of our work.     

How does discourse among like-minded individuals affect their thinking about a complex issue?

Is there reason to be concerned about what has been seen as an increasing trend for discourse on complex issues to be confined to an “echo chamber” of like-minded individuals? To investigate how thinking regarding an issue changes in form following concentrated discourse with like-minded peers, we undertook a qualitative examination of changes in the reasoning that 34 older adults used to justify their positions prior to and following such discourse. They showed a divergence of patterns. A minority abandoned mention of previously expressed ideas at odds with their own positions or otherwise narrowed the reasoning used to justify their positions. Consistent with findings from previous studies, only a minority showed increased certainty and/or extremity (polarisation) on quantitative scales. Countering this minority were a larger proportion whose thinking appeared to benefit from such engagement in several respects that we describe. A follow-up study compares results for a sample of young adults.     

Reasoning and normative beliefs: not too sophisticated

Does reasoning to a certain conclusion necessarily involve a normative belief in support of that conclusion? In many recent discussions of the nature of reasoning, such a normative belief condition is rejected. One main objection is that it requires too much conceptual sophistication and thereby excludes certain reasoners, such as small children. I argue that this objection is mistaken. Its advocates overestimate what is necessary for grasping the normative concepts required by the condition, while seriously underestimating the importance of such concepts for our most fundamental agential capacities. Underlying the objection is the observation that normative thoughts do not necessarily cross our minds during reasoning. I show that proponents of the normative belief condition can accommodate this observation by taking the required normative belief to guide the reasoning process and offer a novel account of what such guidance consists in.     

Design and implementation of domain-specific cognitive system based on question similarity algorithm

The cognitive system is an artificial intelligence product that integrates natural language processing techniques. The biggest d on logical reasoning, which can help users improve exploration and accelerate discovery. On the basis of natural language processing and logical reasoning, the paper adopts similarity algorithm bas difference between big data analysis systems and cognitive systems is that cognitive systems can directly deal with the problems raised by natural language forms and provide predictions baseded on question sentences, designs a cognitive system for specific domains, and finally realizes it on the NAO robot platform.