Perceived leader integrity: Supporting the construct validity and utility of a multi-dimensional measure in two samples

The empirical study of perceived leader integrity has lagged its intuitively appealing role as a fundamental characteristic of effective leaders. Following theoretical examinations of the definition of integrity and previous work arguing that perceived integrity emerges from judgments of leader consistency and leader morality, we developed a multidimensional measure that includes both perceived morality and consistency items. In a first sample of university students, confirmatory factor analyses and results from regression analyses relating the dimensions to direct measures of leader integrity and trust offer partial support for the utility of including dimensions of moral behavior and consistency (represented by behavioral integrity). Further, we replicated these findings in a second sample of working professionals and found support for our hypotheses showing that dimensions assessing behavioral integrity and moral behavior related to leader effectiveness, job satisfaction, work engagement, and intent to quit as mediated by trust in the leader.     

Nondrinker Mortality Risk in the United States

The literature has shown that people who do not drink alcohol are at greater risk for death than light to moderate drinkers, yet the reasons for this remain largely unexplained. We examine whether variation in people’s reasons for nondrinking explains the increased mortality. Our data come from the 1988–2006 National Health Interview Survey Linked Mortality File (N = 41,076 individuals age 21 and above, of whom 10,421 died over the follow-up period). The results indicate that nondrinkers include several different groups that have unique mortality risks. Among abstainers and light drinkers the risk of mortality is the same as light drinkers for a subgroup who report that they do not drink because of their family upbringing, and moral/religious reasons. In contrast, the risk of mortality is higher than light drinkers for former drinkers who cite health problems or who report problematic drinking behaviors. Our findings address a notable gap in the literature and may inform social policies to reduce or prevent alcohol abuse, increase health, and lengthen life.     

Computer tools for statistical quality control

Since the 1920' sanduntil recently, numerical computation has beena limiting factor in the application of statistical methods to the improvement of product quality. This restriction is be in geliminated by the in troduction of computer tools for statistical quality control.

Both novice and expertusers of statistical methods can ben-efitsubstantially from the availability o intergrated soft ware for computing, graphics, and data management. Theuse of such soft ware in SQC training program senables the student to focus on the under standing of statistical techniques, rather than the irmechanicaldetails. In productionen vironments, properly designedinterfaces facilitated at aent ryand access to statistical soft ware by plant personnel, with out requiring know ledge of a computer language. The sesame tool scan be used by management to retrieve in for mationandob tain summaries and display sofcriti-caldata gatheredover different period softime. Finally, computer tool sprovide the applied statistician with agreater range of advanced methods, includinganalytical and graphical extensions of the traditional She whart control chart.     

Gender Differences in Mental Well-Being: a Decomposition Analysis

The General Health Questionnaire (GHQ) is frequently used as a measure of mental well-being. A consistent pattern across countries is that women report lower levels of mental well-being, as measured by the GHQ. This paper applies decomposition techniques to Irish data for 1994 and 2000 to examine the factors lying behind the gender differences in GHQ score. For both 1994 and 2000 about two-thirds of the raw difference is accounted for by differences in characteristics, with employment status the single most important factor.     

Speech Content and the Emergence of Inequality in Task Groups

We examine how the content of actors' speech and the frequency with which they make contributions affect the emergence and legitimation of inequality in task groups. Previous research has focused on classifying acts, the smallest meaningful units of speech, such as providing opportunities to others to speak, making task relevant suggestions, and positively or negatively evaluating the contributions of others. We also employ a classification scheme based on the cognitive complexity of spoken language in the turn. This scheme is based on an interpretation of the cognitive development model posited by Piaget. In addition to the complexity of language, we analyze speech group members employ to organize to solve the task. These classifications rely on the entire content of the turn rather than the more atomistic act. Data analyzed are from 33 groups of students performing different types of tasks. We employ structural equation models to identify how acts and content are related to one another in the observed interaction patterns in groups. Applications of these insights are explored in the discussion.     

Dirty money: Is there a wage premium for working in a pollution intensive industry?

Within a compensating wage differential framework we investigate whether there is a wage premium for working in a pollution intensive industry. Our results for the economy as a whole suggest a small wage premium of approximately one quarter of one percent associated with the risk of working in a dirty job. This premium rises to over fifteen percent for those individuals who work in one of the five dirtiest industries. We also find evidence of a fatal risk wage premium, providing estimates of the value of a statistical life of between ￡12 million and ￡19 million (2000 prices).     

Understanding the Downshifting Phenomenon: A Case of South East Queensland,Australia

A quality of life survey of a sample of households across the Brisbane‐South East Queensland region has identified about 28 percent of people as ‘downshifters.‘ They are defined as people who voluntarily make a long‐term change in their lifestyle – other than planned retirement – which reduces income and adjusts their lifestyle conditions. A typology of downshifters is developed on the basis of their motives for downshifting and their socio‐economic and demographic characteristics using a Two Step Cluster Analysis. Results indicate that the social and economic circumstances and the reasons and methods of downshifting tend to vary substantially across the clusters.