What do men and women want in a partner? Are educated partners always more desirable?

Previous research has shown that males value a potential partner’s physical attractiveness more than females do, whereas females value a potential partner’s socioeconomic status (SES) more than males do. But are men really so unconcerned about a potential partner’s SES? Five studies revealed that men do integrate information about a woman’s SES into their decisions on whether to consider her as a romantic partner or not. Results consistently demonstrated that male participants preferred women with lower SES. Female participants, in contrast, preferred men with higher SES. These sex differences were more pronounced when a long-term romantic relationship rather than a one-night stand was being considered. In addition, men’s lower reported likelihood of romantic contact with a woman with high SES was due to her high educational level rather than her high income. Mediational analyses showed that men perceived a potential partner with high educational level as less likeable and less faithful, and thus reported less likelihood of romantic contact.     

具有认知诊断功能的计算机化自适应测验的研究与实现

构造具有认知诊断功能的计算机化自适应测验（Computerized Adaptive Testing,CAT）,关键在于设计不同于传统CAT的选题策略。本文采用先认知诊断后估计能力的方法,在诊断阶段用状态转换图描述特定认知领域中所有知识状态及这些状态之间的联系,以图的深度优先算法为基础设计选题策略;而在能力估计精细化阶段,每个被试所测项目,不仅与其能力估计值相匹配,且只与其所掌握的属性相关。本文采用蒙特卡罗模拟针对三种不同的属性结构进行试验,结果良好     

进化心理学概览

该文认为处于萌芽状态的进化心理学作为一个新的心理学分支学科对人类心理运行机制提出了一些基本的解释与预测。该文也讨论了进化心理学研究遭受到的两种批评,其一是文化的重要性没有得到重视;其二是进化历史是“假想的故事”。同时作者认为完整地理解心理学研究课题需要进行最终水平的因果分析,只有掌握与运用自然选择理论才能从最终水平上理解研究课题     

A Bayesian approach to the evolution of perceptual and cognitive systems

We describe a formal framework for analyzing how statistical properties of natural environments and the process of natural selection interact to determine the design of perceptual and cognitive systems. The framework consists of two parts: a Bayesian ideal observer with a utility function appropriate for natural selection, and a Bayesian formulation of Darwin's theory of natural selection. Simulations of Bayesian natural selection were found to yield new insights, for example, into the co‐evolution of camouflage, color vision, and decision criteria. The Bayesian framework captures and generalizes, in a formal way, many of the important ideas of other approaches to perception and cognition.     

TEILHARD DE CHARDIN'S EVOLUTIONARY NATURAL THEOLOGY

Pierre Teilhard de Chardin develops, as is well known, a model of evolution as a convergent progression from primordial multiplicity through increasing degrees of complexity toward a final Omega point of spiritual consummation. I explore how Teilhard fuses Darwinian and Lamarckian theories of evolution in developing his own, and in particular his defense of the view that Lamarckism is fundamental to a proper understanding of evolution's human phase. Teilhard's scientific interpretation of evolution is inspired by Christian cosmological insights derived from patristic theology and contemporary Pauline scholarship and cannot be separated from them. His integration of science and theology provides the basis for a renewed evolutionary natural theology that supplants the traditional static models developed by William Paley and others. Teilhard's natural theology also provides a framework for theological ethical reflection on how humanity should act in its capacity as created co‐creator with God. In later work, he considers the implications of his evolutionary theology for the wider universe. Teilhard thus presents an invigorated natural theology grounded in evolution that confirms and completes a dynamic and teleological view of the cosmos.     

Stochastic search item selection for factor analytic models

In this paper we implement a Markov chain Monte Carlo algorithm based on the stochastic search variable selection method of George and McCulloch (1993) for identifying promising subsets of manifest variables (items) for factor analysis models. The suggested algorithm is constructed by embedding in the usual factor analysis model a normal mixture prior for the model loadings with latent indicators used to identify not only which manifest variables should be included in the model but also how each manifest variable is associated with each factor. We further extend the suggested algorithm to allow for factor selection. We also develop a detailed procedure for the specification of the prior parameters values based on the practical significance of factor loadings using ideas from the original work of George and McCulloch (1993). A straightforward Gibbs sampler is used to simulate from the joint posterior distribution of all unknown parameters and the subset of variables with the highest posterior probability is selected. The proposed method is illustrated using real and simulated data sets.     

Converting interns into regular employees: The role of intern–supervisor exchange

Internship participation has undergone rapid expansion over the past three decades, to a point where today, many graduates and internship host-organisations regard internships as the preferred career entry point into a range of professional vocations. To date, however, there has been a dearth of studies examining factors that can influence the conversion of interns into regular employees with their host-organisations. This study bridges that gap as it involved the collection of data at three time intervals from 303 intern–supervisor dyads (n = 606), in order to determine the key predictors of intern conversion. Findings indicated that although intern–supervisor exchange played a strong role in influencing intern's performance, learning opportunities and satisfaction it did not play a significant role in predicting both the intern's and the supervisor's conversion intentions. Nonetheless, both intern's and supervisor's conversion intentions measured during the internship period did play a strong role in predicting actual conversion to employment at the host-organisation subsequent to the intern's graduation. Thus, this study begins to shed light on the dynamics on intern conversion, as a pivotal early juncture in an employee's career lifespan.     

Response-repetition effects depend on motor set: Evidence for anatomical coding in response selection

Successful motor performance requires a process of response selection that chooses the correct response out of a set of possible ones. Most theories of response selection assume that this selection process operates on spatial codes, which define the location of stimuli and responses in environmental coordinates, with little or no role for the anatomical codes of the effectors involved. In this study, we tested this assumption by investigating response-repetition effects in a response-cuing paradigm using two motor sets (fingers on one hand vs. fingers on two hands). Reaction time results demonstrated a robust response-repetition benefit that was greater for the one-hand set than for the two-hands set. Furthermore, with the one-hand set the repetition benefit was independent of cue type and cue-stimulus interval on the previous trial, whereas with the two-hands set it was strongly modulated by these two factors. These differential response-repetition effects for one- and two-hands motor sets demonstrate the important role of the neuro-anatomical hand distinction in response selection, thereby supporting multiple coding notions.     

ALTRUISM AND THE GOLDEN RULE

This essay addresses recent claims about the compatibility of the sociobiological theory of reciprocal altruism with standard Western formulations of the Golden Rule. Derek Parfit claims that the theory of reciprocal altruism teaches us to be “reciprocal altruists,” who benefit only those people from whom we can reasonably expect benefits in the future. The Golden Rule, on the other hand, teaches us to benefit anyone regardless of their intention or ability to return the favor, or as Parfit puts it, the Golden Rule teaches us to be “suckers.” I argue that this distinction is founded on a misconception of the nature of the theory of reciprocal altruism, which is sociobiological as opposed to moral, and that this distinction accordingly confuses is with ought. Sociobiological theories may explain underlying psychological motivations in individuals (and perhaps even in populations), but these theories do not prescribe any sort of moral behavior. Furthermore, the theory of reciprocal altruism does not imply mental states of which agents are aware. The unconscious motivations assumed by this theory are in fact compatible with certain formulations of the Golden Rule; I will accordingly argue for the view that certain words with moral content related to the Golden Rule—such as “altruism” and “selfishness”—exist only insofar as they are social tools, which can further the self‐interests of an individual in any group.     

Development of a Cyber/Information Technology Knowledge Test for Military Enlisted Technical Training Qualification

An Armed Services Vocational Aptitude Battery (ASVAB) Review Panel, with expertise in personnel selection, job classification, psychometrics, and cognitive psychology developed recommendations for changes to the military enlistment test battery. One recommendation was to develop and evaluate a test of cyber/information and communications technology literacy to supplement current ASVAB content. This article summarizes a multiphased Cyber Test development process: (a) a review of information/computer technology literacy definitions and measures, (b) development and pilot testing of a cyber knowledge measure, (c) validation of test scores against final school grades (FSGs) for selected technical training courses, (d) development of an operational reporting metric and subgroup norms, and (e) examination of construct validity. Results indicate the Cyber Test has predictive validity versus technical training school grades and incremental validity comparable to the ASVAB technical knowledge tests when used with the ASVAB Armed Forces Qualification Test (AFQT) verbal/math composite as a baseline.