When Working Hard Is Not Enough for Female and Racial/Ethnic Minority Apprentices in the Highway Trades

Drawing on employment records, qualitative interviews, and a survey, we explore the experiences of apprentices in the highway trades in Oregon. We demonstrate that female and racial/ethnic minority apprentices have lower rates of recruitment and retention and disproportionately face challenges with interpersonal interactions, hiring practices, and supervisory practices. Yet, we find a pervasive narrative that attributes apprentices' success to “hard work,” which contributes to the legitimacy of these inequalities. Consistent with the conceptualization of work organizations as inequality regimes, we argue that the apprenticeship system has policies, practices, and ideologies that are on the surface gender and race/ethnicity neutral, yet lead to the perpetuation of inequalities.     

A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

Liminality in Management and Organization Studies: Process,Position and Place

This paper explores liminality, a concept receiving increased attention in management and organization studies and gaining prominence because of its capacity to capture the interstitial and temporary elements of organizing and work. The authors present a systematic review of the literature on liminality, covering 61 published papers, and undertake a critical analysis of how the concept of liminality has been used in prior research. This review reveals associations with three main themes: process; position; and place. For each theme, the authors identify the central research questions posed, while comparing individual and collective levels of analysis. During this process, the authors revisit several ideas central to the original, anthropological research on liminality, a perspective from which they suggest a rejuvenation of liminality research in management and organization studies. This paper argues for a greater focus on the liminal experience itself – especially its ritual and temporal dimensions – and for improving the comparative analysis of liminality following the three themes identified in this paper. The authors suggest that revising the agenda for liminality research along these lines could facilitate more informed responses to the challenges of an increasingly temporary and dynamic work life.     

Can Children Recognize Bodily Expressions of Emotion?

Journal of Nonverbal Behavior - Past research has demonstrated that children understand distinct emotion concepts and can accurately recognize facial expressions of distinct emotions by a young...     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Media Disaster Reporting Effects on Public Risk Perception and Response to Escalating Tornado Warnings: A Natural Experiment

Previous research has evaluated public risk perception and response to a natural hazards in various settings; however, most of these studies were conducted either with a single scenario or after a natural disaster struck. To better understand the dynamic relationships among affect, risk perception, and behavioral intentions related to natural disasters, the current study implements a simulation scenario with escalating weather intensity, and includes a natural experiment allowing comparison of public response before and after a severe tornado event with extensive coverage by the national media. The current study also manipulated the display of warning information, and investigated whether the warning system display format influences public response. Results indicate that (1) affect, risk perception, and behavioral intention escalated as weather conditions deteriorated, (2) responses at previous stages predicted responses at subsequent stages of storm progression, and (3) negative affect predicted risk perception. Moreover, risk perception and behavioral intention were heightened after exposure to the media coverage of an actual tornado disaster. However, the display format manipulation did not influence behavioral responses. The current study provides insight regarding public perception of predisaster warnings and the influence of exposure to media coverage of an actual disaster event.     

Developing a Broadly Applicable Measure of Risk Perception

Decades of research identify risk perception as a largely intuitive and affective construct, in contrast to the more deliberative assessments of probability and consequences that form the foundation of risk assessment. However, a review of the literature reveals that many of the risk perception measures employed in survey research with human subjects are either generic in nature, not capturing any particular affective, probabilistic, or consequential dimension of risk; or focused solely on judgments of probability. The goal of this research was to assess a multidimensional measure of risk perception across multiple hazards to identify a measure that will be broadly useful for assessing perceived risk moving forward. Our results support the idea of risk perception being multidimensional, but largely a function of individual affective reactions to the hazard. We also find that our measure of risk perception holds across multiple types of hazards, ranging from those that are behavioral in nature (e.g., health and safety behaviors), to those that are technological (e.g., pollution), or natural (e.g., extreme weather). We suggest that a general, unidimensional measure of risk may accurately capture one's perception of the severity of the consequences, and the discrete emotions that are felt in response to those potential consequences. However, such a measure is not likely to capture the perceived probability of experiencing the outcomes, nor will it be as useful at understanding one's motivation to take mitigation action.     

Beyond Piketty: A new perspective on poverty and inequality in India

The socio-economic literature has focused much on how overall inequality in income distribution (frequently measured by the Gini coefficient) undermines the “trickle down” effect. In other words, the higher the inequality in the income distribution, the lower is the growth elasticity of poverty. However, with the publication of Piketty’s magnum opus (2014), and a subsequent study by Chancel and Piketty (2017) of evolution of income inequality in India since 1922, the focus has shifted to the income disparity between the richest 1% (or 0.01%) and the bottom 50%. Their central argument is that the rapid growth of income at the top end of millionaires and billionaires is a by-product of growth. The present study extends this argument by linking it to poverty indices in India. Based on the India Human Development Survey 2005–12 – a nationwide panel survey-we examine the links between poverty and income inequality, especially in the upper tail relative to the bottom 50%, state affluence (measured in per capita income) and their interaction or their joint effect. Another feature of our research is that we analyse their effects on the FGT class of poverty indices. The results are similar in as much as direction of association is concerned but the elasticities vary with the poverty index. The growth elasticities are negative and significant for all poverty indices. In all three cases, the disparity between the income share of the top 1% and share of the bottom 50% is associated with greater poverty. These elasticities are much higher than the (absolute) income elasticities except in the case of the poverty gap. The largest increase occurs in the poverty gap squared – a 1% greater income disparity is associated with a 1.24% higher value of this index. Thus the consequences of even a small increase in the income disparity are alarming for the poorest.