决策者角色及相关变量对风险偏好的影响

采用IAT技术测查被试的内隐自尊, 并引入收益和损失两种任务框架, 综合探讨了内隐自尊水平、任务得失框架对自我决策和为他人决策时风险偏好的影响。结果发现：(1)在收益框架下, 被试为他人决策时更冒险, 而在损失框架下, 为自我和他人决策的风险偏好无显著差异; (2)与为自我决策相比, 低内隐自尊者为他人决策时更冒险, 而高内隐自尊者为自我和他人决策的风险偏好无显著差异; (3)内隐自尊水平与任务框架的交互作用及内隐自尊水平、任务框架和决策者角色之间的三级交互作用均不显著。依据相关的理论和发现对这种结果进行了分析和讨论。     

Fertile women are more demanding: Ovulatory increases in minimum mate preference criteria across a wide range of characteristics and relationship contexts

The ovulatory shift hypothesis (Gangestad, Thornhill, & Garver-Apgar, 2005) makes three predictions. First, it posits that during peak fertility, women are more attracted to males who display characteristics of good genes. Secondly, it predicts that women predominantly experience ovulatory shifts when evaluating males as short-term sexual partners. Lastly, it predicts that ovulatory shifts should be non-existent when measuring mate preferences associated with long-term partner quality. However given that female preferences are formulated as a means to offset costs associated with reproduction (Buss, 1994) and such costs are more likely to be incurred during peak fertility, the current study (via the ovulatory reproductive safeguards hypothesis) posits that women during peak fertility should show a general increase in their mate preference criteria across a variety of characteristics and relationships. Using a within-subjects design and hormonal markers of fertility status, the present study investigates the degree to which ovulatory shifts in preferences are limited to short-term sexual liaisons and the degree to which such shifts are associated with characteristics related to long-term partner quality. Contrary to the ovulatory shift hypothesis (and in support of the ovulatory reproductive safeguards hypothesis), ovulatory shifts were found across a wide range of relationship contexts and preference characteristics.     

区域文化与区域刻板印象的心理学研究范式

区域刻板印象(regional stereotype)是一种涉及知觉者的关于某个地区人群群体的知识、观念与预期的认知结构。区域刻板化既是自然环境的产物,也是社会文化的产物,区域刻板化的形成既有心理因素,也有社会因素、个体因素。     

Statistical models for the induction and use of selectional preferences

Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach has surfaced in the computational linguistics community. This new line of research combines knowledge represented in a pre‐defined semantic class hierarchy with statistical tools including information theory, statistical modeling, and Bayesian inference. These tools are used to learn selectional preferences from examples in a corpus. Instead of simple sets of semantic classes, selectional preferences are viewed as probability distributions over various entities. We survey research that extends Resnik's initial work, discuss the strengths and weaknesses of each approach, and show how they together form a cohesive line of research.     

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.     

Do we make decisions for other people based on our predictions of their preferences? evidence from financial and medical scenarios involving risk

Abstract

The ways in which the decisions we make for others differ from the ones we make for ourselves has received much attention in the literature, although less is known about their relationship to our predictions of the recipient’s preferences. The latter question is of particular importance given real-world occurrences of surrogate decision-making which require surrogates to consider the recipient’s preferences. We conducted three experiments which explore this relationship in the medical and financial domains. Although there were mean discrepancies between surrogate predictions and choices, we identified a predictive relationship between the two. Moreover, when participants took high risks for themselves, it seems that they were not willing to do so for others, even when they believed that the recipient’s preferences were similar to their own. We discuss these findings relative to current theories and real-world instances of surrogate decision-making.