Hijab in the American workplace: visibility and discrimination

While the initial purpose of this article was to outline online collective action (OCA) towards promoting the rights of hijab-wearing Muslim women in the workplace, it became apparent that there were substantial impediments to this solidarity. Thus, the bulk of it takes up these obstacles, arguing that American hijabis face structural discrimination and Muslims in the United States are subjected to heightened discrimination when they are highly visible to the mainstream culture. This article reviews two cases of workplace discrimination against hijabis and the reactions to these incidents on the Huffington Post, Los Angeles Times, and hijab-oriented blogs. Findings indicate that intolerance of Muslims is prevalent across various political affiliations and apprehension associated with hijabi rights could be related to the perceived decline of white privilege. The analysis also demonstrates that there may be impediments to solidarity with hijabi rights within Muslim communities due to disagreements on the Qur’anic mandate of modesty, divergent perspectives on how Muslims can best promote their rights and ensure their safety, and misunderstandings related to the rights guaranteed under reasonable accommodation. Despite the various obstacles to solidarity with hijabis, the article traces various forms of OCA at local, national and international levels that were encountered on social media platforms.     

词素的结构对称效应:结构对称汉语成语认知特点的进一步研究

运用词素启动作业,进一步考察了结构对称性汉语成语的识别过程.结果发现(1)无论是用成语的前二个字还是后二个字启动,在成语识别过程中都存在明显的词素结构对称效应,即结构对称成语中的词素启动效应明显大于非对称成语中的词素启动效应.(2)成语的结构对称性、熟悉度和启动词素位置之间存在显著的三阶相互作用.简单效应的分析表明无论成语前二个字还是后二个字启动,词素的结构对称效应均只在低熟悉度成语的识别过程中显著;在前二个字启动时,非对称成语的识别还存在熟悉度效应.     

A multitrait-multimethod model with minimal assumptions

A new model of confirmatory factor analysis (CFA) for multitrait-multimethod (MTMM) data sets is presented. It is shown that this model can be defined by only three assumptions in the framework of classical psychometric test theory (CTT). All other properties of the model, particularly the uncorrelated-ness of the trait with the method factors are logical consequences of the definition of the model. In the model proposed there are as many trait factors as different traits considered, but the number of method factors is one fewer than the number of methods included in an MTMM study. The covariance structure implied by this model is derived, and it is shown that this model is identified even under conditions under which other CFA-MTMM models are not. The model is illustrated by two empirical applications. Furthermore, its advantages and limitations are discussed with respect to previously developed CFA models for MTMM data.     

Robust mean and covariance structure analysis through iteratively reweighted least squares

Robust schemes in regression are adapted to mean and covariance structure analysis, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is properly weighted according to its distance, based on first and second order moments, from the structural model. A simple weighting function is adopted because of its flexibility with changing dimensions. The weight matrix is obtained from an adaptive way of using residuals. Test statistic and standard error estimators are given, based on iteratively reweighted least squares. The method reduces to a standard distribution-free methodology if all cases are equally weighted. Examples demonstrate the value of the robust procedure.The authors acknowledge the constructive comments of three referees and the Editor that lead to an improved version of the paper. This work was supported by National Institute on Drug Abuse Grants DA01070 and DA00017 and by the University of North Texas Faculty Research Grant Program.     

无均值结构的潜变量交互效应模型的标准化估计

潜变量交互效应建模研究近年来有两项重要进展, 一是提出了潜变量交互效应模型的标准化估计及其计算公式; 二是发现无均值结构模型可以取代传统的有均值结构模型, 建模大为简化。但标准化估计是在传统的有均值结构模型中建立的, 在简化的模型中同样适用吗？本文在无均值结构模型的框架内, 给出了潜变量交互效应模型的标准化形式、计算公式和建模步骤, 并通过模拟研究比较了极大似然和广义最小二乘两种估计方法、配对乘积指标和全部乘积指标两种指标类型, 结果表明, 在计算交互效应的标准化估计时, 应当使用配对乘积指标建模, 并且首选极大似然估计。     

Analysing multisource feedback with multilevel structural equation models: Pitfalls and recommendations from a simulation study

When multisource feedback instruments, for example, 360-degree feedback tools, are validated, multilevel structural equation models are the method of choice to quantify the amount of reliability as well as convergent and discriminant validity. A non-standard multilevel structural equation model that incorporates self-ratings (level-2 variables) and others’ ratings from different additional perspectives (level-1 variables), for example, peers and subordinates, has recently been presented. In a Monte Carlo simulation study, we determine the minimal required sample sizes for this model. Model parameters are accurately estimated even with the smallest simulated sample size of 100 self-ratings and two ratings of peers and of subordinates. The precise estimation of standard errors necessitates sample sizes of 400 self-ratings or at least four ratings of peers and subordinates. However, if sample sizes are smaller, mainly standard errors concerning common method factors are biased. Interestingly, there are trade-off effects between the sample sizes of self-ratings and others’ ratings in their effect on estimation bias. The degree of convergent and discriminant validity has no effect on the accuracy of model estimates. The χ² test statistic does not follow the expected distribution. Therefore, we suggest using a corrected level-specific standardized root mean square residual to analyse model fit and conclude with further recommendations for applied organizational research.     

Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis

Cross validation is a useful way of comparing predictive generalizability of theoretically plausible a priori models in structural equation modeling (SEM). A number of overall or local cross validation indices have been proposed for existing factor-based and component-based approaches to SEM, including covariance structure analysis and partial least squares path modeling. However, there is no such cross validation index available for generalized structured component analysis (GSCA) which is another component-based approach. We thus propose a cross validation index for GSCA, called Out-of-bag Prediction Error (OPE), which estimates the expected prediction error of a model over replications of so-called in-bag and out-of-bag samples constructed through the implementation of the bootstrap method. The calculation of this index is well-suited to the estimation procedure of GSCA, which uses the bootstrap method to obtain the standard errors or confidence intervals of parameter estimates. We empirically evaluate the performance of the proposed index through the analyses of both simulated and real data.     

The Theory of Positive Disintegration through the Lens of Complexity Science

The article introduces the main ideas and concepts of D?browski’s theory of positive disintegration, and then subsequently provides a reconceptualization of this theory by complexity science. According to D?browski, positive disintegration is the mental development described by the process of transition from lower to higher levels of mental life and is stimulated by tension, inner conflict, struggle, and anxiety. This process can be modeled by a sequence of attractors (levels) as a control parameter (a developmental potential) changes and by a process of symmetry breaking. As an application of this theory, a conceptual model of adolescent development is presented.     

Decision making in the prisoner's dilemma game: The effect of exit on cooperation and social welfare

The prisoner's dilemma game is a mixed‐motive game that offers two players the simultaneous choice between a cooperative and a defective alternative. An often neglected aspect of such a binary‐choice game, however, is that in many real‐life encounters, people can choose not only to cooperate or defect, but they also have a third option: to exit the social dilemma. Although in the literature a consensus has emerged that the addition of an exit opportunity benefits cooperation, there is only scant research into its effect on social welfare. In order to allow a direct comparison of cooperation rates and welfare levels across binary‐choice and trinary‐choice games, in this study, we used a design in which the same participants played similar games with and without an exit option (i.e., a within‐subjects design), and this in a range of structural variations. The findings of our study indicated that the aggregated outcome of both players is generally lower in games with an exit option than in games without an exit option. Moreover, our results showed that the efficiency of the exit option strongly depends on the specific outcome structure of the game (in terms of its endowment size, (a)symmetry, and level of noncorrespondence). In the discussion, it is argued that the implementation of an exit option as a strategy to increase social welfare should be critically assessed.