Aggregation of opinions based on correlated cues and advisors

We study the process by which decision makers (DMs) aggregate probabilistic opinions from multiple, correlated sources with a special emphasis on the determinants of the DM's confidence, which is a predictor of the DM's willingness to accept the implications of the aggregation process. Our model assumes that (a) DM combines the advisors' opinions by weighting them according to the amount of information underlying them, and (b) the DM's confidence increases as a function of a variety of factors that reduce the variance of the aggregate. We report results of three studies that manipulate the predictive validity of the cues and their inter‐correlations. Most of the models' predictions are supported but, contrary to the model's prediction, the DMs' confidence is not sensitive to the inter‐cue correlation. The best predictors of the DMs' confidence are the perceived predictability of the event, the level of agreement among the advisors, and the advisors' self‐reports of confidence. This pattern of results is explained by the ‘system neglect’ hypothesis. Copyright © 2006 John Wiley & Sons, Ltd.     

Infant perceptual and conceptual categorization: the roles of static and dynamic stimulus attributes

Infants' categorization of animals and vehicles based on static vs. dynamic attributes of stimuli was investigated in five experiments (N=158) using a categorization habituation-of-looking paradigm. In Experiment 1, 6-month-olds categorized static color images of animals and vehicles, and in Experiment 2, 6-month-olds categorized dynamic point-light displays showing only motions of the same animals and vehicles. In Experiments 3, 4, and 5, 6- and 9-month-olds were tested in an habituation-transfer paradigm: half of the infants at each age were habituated to static images and tested with dynamic point-light displays, and the other half were habituated to dynamic point-light displays and tested with static images. Six-month-olds did not transfer. Only 9-month-olds who were habituated to dynamic displays showed evidence of category transfer to static images. Together the findings show that 6-month-olds categorize animals and vehicles based on static and dynamic information, and 9-month-olds can transfer dynamic category information to static images. Transfer, static vs. dynamic information, and age effects in infant categorization are discussed.     

Are adoption gains on the g factor? A meta-analysis

When children are adopted into prosperous families they generally show IQ gains. The meta-analytic correlation between subtest g loadings and adoption gains is examined (K = 4, combined N = 3018). A number of meta-analytic corrections are applied to the estimate, yielding a correlation of −1. The results are discussed.     

How Revolutionary is the Holy Spirit?

Most theologians agree that the early church neglected the Holy Spirit in formulations of the Trinity, and in recent years, many books have been written to redress this deficiency. Pentecostal theologians are especially invested in recovering a fuller doctrine of the Holy Spirit. These two monographs, one by an established scholar (Steve Studebaker) and the other by a relative newcomer (Andrew Gabriel), are among the best on this topic. Both are unafraid to be critical of Pentecostal theology and both are valuable for their specificity. Gabriel revises the divine attributes of classical theism while Studebaker goes even further by arguing that the Holy Spirit constitutes the Trinity. Neither author is sympathetic to Social Trinitarianism, and Studebaker in particular is critical of Richard of Saint Victor, who is often credited as an early progenitor of the social model. This first complete translation of Richard's treatise on the Trinity, by Ruben Angelici, reveals a radical view of the Holy Spirit and thus needs to be taken seriously by all future discussions of this topic. Richard not only gives the Holy Spirit its own personal identity but also ties the Spirit to God's power of listening, just as the Son is God's Word.     

不同认知成分在图形推理测验项目难度预测中的作用

理解项目难度变异的来源是实现计算机自动化项目生成的第一步。通过文献综述, 总结出影响图形推理测验项目难度的四个方面的因素, 再通过操控构图元素熟悉性、属性的抽象性、知觉组织的和谐性以及规则类型与数目这些因素, 编制8套图形推理测验, 共包含112个与高级瑞文推理类似的项目。采用铆测验等值设计, 在每套测验中嵌入10个高级瑞文推理测验项目为铆题, 通过网络施测于6323名被试。使用BILOG MG估算项目参数, 并使用IRTEQ进行测验等值, 将后七套测验上所有项目的项目参数都转换到第一套测验的单位系统上。以项目难度为因变量, 项目题干特征变量为预测变量进行回归分析, 结果发现这四个因素均对项目难度有显著预测作用。优势分析的结果显示记忆负荷(即规则类型与数目的组合)是项目难度的最重要的预测变量, 其他依次为属性的抽象性、知觉组织的和谐性和构图元素熟悉性。     

Rough approximation of pairwise comparisons described by multi‐attribute stochastic dominance

Given a finite set A of actions evaluated by a set of attributes, preferential information is considered in the form of a pairwise comparison table including pairs of actions from subset B⊂A described by stochastic dominance relations on particular attributes and a total order on the decision attribute. Using a rough sets approach for the analysis of the subset of preference relations, a set of decision rules is obtained, and these are applied to a set A\B of potential actions. The rough sets approach of looking for the reduction of the set of attributes gives us the possibility of operating on a multi‐attribute stochastic dominance for a reduced number of attributes. Copyright © 1999 John Wiley & Sons, Ltd.