态度及其与行为模式述评

态度一直是社会心理学的核心问题,态度对于预测行为具有重要作用。本文阐述了态度的界定、态度的结构模型及态度预测行为模型的各种理论,在这些理论的基础上,提出了态度预测行为的另一模型。     

Different Effects of Cognitive Shifting and Intelligence on Creativity

The relationship between creativity and executive control has long been controversial. Some researchers view creative thinking as a defocused process with little executive control involvement, whereas others claim that executive control plays a vital role in creative thinking. In this study, we focused on one subcomponent of executive control, cognitive shifting, and examined its relationship with creativity by using latent variable analysis and structural equation modeling. We also analyzed whether this relation was mediated by intelligence. The results showed that: (a) cognitive shifting ability had a positive relationship with creativity, but only on the quantitative aspects (fluency and flexibility); (b) Intelligence had a positive relationship with both quantitative and qualitative aspects (originality) of creativity, and its effect on qualitative aspect was stronger than that on the quantitative aspect; (c) There was a mediating effect of intelligence on the relationship between creativity cognitive and shifting.     

Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data

A general latent variable modeling framework called n-Level Structural Equations Modeling (NL-SEM) for dependent data-structures is introduced. NL-SEM is applicable to a wide range of complex multilevel data-structures (e.g., cross-classified, switching membership, etc.). Reciprocal dyadic ratings obtained in round-robin design involve complex set of dependencies that cannot be modeled within Multilevel Modeling (MLM) or Structural Equations Modeling (SEM) frameworks. The Social Relations Model (SRM) for round robin data is used as an example to illustrate key aspects of the NL-SEM framework. NL-SEM introduces novel constructs such as ‘virtual levels’ that allows a natural specification of latent variable SRMs. An empirical application of an explanatory SRM for personality using xxM, a software package implementing NL-SEM is presented. Results show that person perceptions are an integral aspect of personality. Methodological implications of NL-SEM for the analyses of an emerging class of contextual- and relational-SEMs are discussed.     

Accounting for Missing Correlation Coefficients in Fixed-Effects MASEM

Meta-analytic structural equation modeling (MASEM) is increasingly applied to advance theories by synthesizing existing findings. MASEM essentially consists of two stages. In Stage 1, a pooled correlation matrix is estimated based on the reported correlation coefficients in the individual studies. In Stage 2, a structural model (such as a path model) is fitted to explain the pooled correlations. Frequently, the individual studies do not provide all the correlation coefficients between the research variables. In this study, we modify the currently optimal MASEM-method to deal with missing correlation coefficients, and compare its performance with existing methods. This study is the first to evaluate the performance of fixed-effects MASEM methods under different levels of missing correlation coefficients. We found that the often used univariate methods performed very poorly, while the multivariate methods performed well overall.     

Authentic leadership,followership, and psychological capital as antecedents of work engagement

The present study investigated authentic leadership, psychological capital, and followership behaviour influences on work engagement of employees. Respondents were 901 South African employees within the healthcare industry organisation (n = 647) and mining industry (n = 254). The employees completed questionnaires on authentic leadership, psychological capital, and followership behaviour, and work engagement. Results following structural equation modelling and mediation analysis suggest work engagement to be explained by the psychological capital of the employee rather than by authentic leadership qualities. Improving employee psychological capital has the potential to enhance the levels of work engagement of employees.     

Accuracy and performance of the state-based Φ and liveliness measures of information integration

A number of people have suggested that there is a link between information integration and consciousness, and a number of algorithms for calculating information integration have been put forward. The most recent of these is Balduzzi and Tononi’s state-based Φ algorithm, which has factorial dependencies that severely limit the number of neurons that can be analyzed. To address this issue an alternative state-based measure known as liveliness has been developed, which uses the causal relationships between neurons to identify the areas of maximum information integration. This paper outlines the state-based Φ and liveliness algorithms and sets out a number of test networks that were used to compare their accuracy and performance. The results show that liveliness is a reasonable approximation to state-based Φ for some network topologies, and it has a much more scalable performance than state-based Φ.     

Developmental models for children's temperament: alternatives to chronometric polynomial curves

Partridge and Lerner (2007), in a secondary analysis of the New York Longitudinal Study, employed a chronometric polynomial growth curve model to argue that the developmental course of difficult temperament follows a non‐linear trajectory over the first 5 years of life. The free curve slope intercept (FCSI) growth curve model of Meredith and Tisak (1990) is presented as a preferable conceptual alternative because it contains a number of currently popular statistical models, including repeated measures multivariate analysis of variance, factor mean, linear growth, linear factor analysis, and hierarchical linear models as special cases. As such, researchers can compare the fit of each of these models relative to the FCSI model, and, at times, to each other. The present paper conducts a re‐analysis of the data, and establishes that fit of the FCSI model is arguably better than other statistical alternatives. The FCSI model is also used as the basis for identifying subgroups of individuals with their qualitatively distinct growth patterns within a growth mixture modeling framework. Copyright © 2010 John Wiley & Sons, Ltd.     

Does ordinary injustice make extraordinary injustice possible? Gender,structural injustice,and the ethics of refugee determination

Our understanding of the impact of gender on refugee determination has evolved greatly over the last 60 years. Though many people initially believed that women could not be persecuted qua women, it is now frequently recognized that certain forms of gender-related persecution are sufficient to warrant asylum. Yet despite this conceptual progress, many states are still reluctant to consider certain forms of gender-related persecution to be sufficient to warrant asylum or refugee status. One reason for this continued bias is the lack of a framework with which to understand gender-related persecution. I argue that we ought to understand gender-related persecution as resulting from the intersection of individual or state persecution and structural injustice. Structural injustice can be understood as the kind of everyday injustice, harm, and violence that women experience that makes possible the more extraordinary kinds of violence that women are likely to claim as the basis of asylum. Understanding gender-related persecution within the context of structural injustice will, I argue, help us to see it as a legitimate form of persecution and thus allow more just outcomes for women refugees.