实践社区成员的成就动机对知识传播的影响

为了研究成就动机对实践社区及其成员的知识传播过程的影响,采用自编实践社区成员成就动机问卷以及知识传播过程与效果问卷对重庆、银川、南京、上海等地企业的430名实践社区成员进行测量,研究了成就动机对知识传播的影响.结果表明:问卷具有良好的信度和效度;不同性别被试的社会取向成就动机存在显著差异;工作年限为11-15年的被试社会取向成就动机识显著高于其他组别;自我取向成就动机对知识传播的路径系数除"自我取向-区内吸收"外均达到显著性水平,即对"知识传播投入程度"、"社区外知识获取能力"及"知识传播效果"的预测作用都是正向的;社会取向成就动机仅对知识传播效果产生显著影响.     

目标类别空间关系判断任务中的提示效应

研究采用"提示-目标"的范式,探讨不同范围区域性提示对类别空间关系判断任务的影响,以期丰富已有的研究成果.研究结果发现:在类别空间关系判断任务中同样存在注意的提示效应,而且提示范围的效用程度影响被试在任务中的反应效率,另外这种提示效应还受到任务特性和背景刺激中存在的空间关系的影响.     

句子语境中汉语词汇歧义消解的眼动研究

采用眼动方法.通过两个实验考察了汉语同音同形歧义词的歧义消解过程.结果显示:(1)在中性句子语境中,均衡歧义词的首视时间显著高于偏向歧义词.歧义词的意义通达仅受歧义词意义的相对频率影响,不受语境的影响;(2)在偏向句子语境中,当语境支持歧义词的次要意义时,被试对偏向歧义词的解歧信息的注视时间显著高于其他两类目标词,体现了语境对歧义词意义的整合作用.实验结果支持词汇歧义消解的模块化模型的观点.     

Loneliness in Infancy: Harry Harlow, John Bowlby and Issues of Separation

In this contribution, the authors give an overview of the different studies on the effect of separation and deprivation that drew the attention of many in the 1940s and 1950s. Both Harlow and Bowlby were exposed to and influenced by these different studies on the so called ‘hospitalization’ effect. The work of Bakwin, Goldfarb, Spitz, and others is discussed and attention is drawn to films that were used to support new ideas on the effects of maternal deprivation.

国外社会心理学领域中主观幸福感的研究进展

社会心理学领域扩展与深化了现代主观幸福感的研究。本文介绍了国外社会心理学领域中有关主观幸福感研究的5个方面的新进展：适应与主观幸福感、记忆与主观幸福感、消极因素与主观幸福感、友好关系与主观幸福感、文化与主观幸福感,勾画出了幸福感的完整风貌,增进了心理学对主观幸福感的理解。     

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares

Data in psychology are often collected using Likert‐type scales, and it has been shown that factor analysis of Likert‐type data is better performed on the polychoric correlation matrix than on the product‐moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real‐data example indicates that estimates by ridge GLS are 9–20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich‐type standard errors following the ridge GLS methods also perform reasonably well.     

Evaluating increased effort for item disposal to improve recycling at a university

An evaluation of increased response effort to dispose of items was conducted to improve recycling at a university. Signs prompting individuals to recycle and notifying them of the location of trash and recycling receptacles were posted in each phase. During the intervention, trashcans were removed from the classrooms, and one large trashcan was available in the hallway next to the recycling receptacles. Results showed that correct recycling increased, and trash left in classrooms increased initially during the second intervention phase before returning to baseline levels.     

Empirically Corrected Rescaled Statistics for SEM with Small N and Large p

Survey data often contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. With typical nonnormally distributed data in practice, a rescaled statistic T_rml proposed by Satorra and Bentler was recommended in the literature of SEM. However, T_rml has been shown to be problematic when the sample size N is small and/or the number of variables p is large. There does not exist a reliable test statistic for SEM with small N or large p, especially with nonnormally distributed data. Following the principle of Bartlett correction, this article develops empirical corrections to T_rml so that the mean of the empirically corrected statistics approximately equals the degrees of freedom of the nominal chi-square distribution. Results show that empirically corrected statistics control type I errors reasonably well even when N is smaller than 2p, where T_rml may reject the correct model 100% even for normally distributed data. The application of the empirically corrected statistics is illustrated via a real data example.     

The Pragmatics of Slurs

I argue that the offense generation pattern of slurring terms parallels that of impoliteness behaviors, and is best explained by appeal to similar purely pragmatic mechanisms. In choosing to use a slurring term rather than its neutral counterpart, the speaker signals that she endorses the term (and its associations). Such an endorsement warrants offense, and consequently slurs generate offense whenever a speaker's use demonstrates a contrastive preference for the slurring term. Since this explanation comes at low theoretical cost and imposes few constraints on an account of the semantics of slurs, this suggests that we should not require semantic accounts to provide an independent explanation of the offense profile.