Responding to environmental change in longshoring: Four north American experiences

In longshoring, technological change, expanding competition among ports, and the development of lower cost work forces induced a major restructuring of dock operations. This paper focuses on collective bargaining responses to environmental change and the interplay between those responses, government intervention, the law, and market forces. Four coastal regions in the United States and Canada are studied to gain a broad perspective in two jurisdictions with somewhat differing approaches to government intervention and labor law. Market pressures have become a dominant force, altering the need for and nature of government intervention, and accommodation to change seems most appropriate in today’s highly competitive marketplace. We are indebted to those we interviewed: Brian Ciccozzi, D. P. (Don) Garcia, Terry Lane, Arnold E. Masters, Gene Vrana, Greg Storey, Joe Weiler, and R. V. Wilds. We greatly appreciate the comments of Vitor Marciano, Yoni Reshef, and an anonymous referee, as well as the support of the Social Sciences and Humanities Research Council and the Rice Fellowship. I thank the Oakland University Research Committee for grant support.     

The poisson-inverse gaussian disiribuiion as a model for species abundance

An inverse Gaussian mixture of Poisson distributions(the P-IG distribution) is considered as a model for species abundance data,, Minimum chi-square and maximum likelihood methods of estimation for the zero-truncated P-IG distribution are developed, Ihe performance of the P-IG distribution is illustrated and discussed for several well-known sets of insect abundance data.     

The Opportunities and Constraints to Collaboration in Public Sector Management

Public Organization Review - This article synthesizes current insights about the opportunities and constraints to collaborative public management. Despite the swath of research on...     

Personality Disorders Among Pathological Gamblers

The objective of this study was to investigate the prevalence of DSM-III-R diagnostic categories of personality disorders in pathological gamblers and to highlight the possible association between such disorders, psychological distress and selected forms of gambling. The Personality Disorders Questionnaire-Revised and a battery of psychometric measures were administered to a sample of 82 consecutive admissions to a behavioral treatment program for gambling problems at an impulse control disorders research unit in Sydney, Australia. Seventy-three percent of subjects were male. The total sample reported having gambled a mean of 15 years of which, on average, the last 6.4 years were associated with problems. Results indicated that the majority of subjects met diagnostic criteria for at least one Personality Disorder (93%), with an average of 4.6 personality disorders per subject. The majority of gamblers evidenced personality disorders from the Cluster B grouping with particularly high rates of borderline, histrionic, and narcissistic personality disorders which were found to be associated with high levels of impulsivity and affective instability. Antisocial personality disorder and narcissistic personality disorder were both found to be possible mediators of the severity of the problem gambling behaviours.     

Online patient feedback as a safety valve: An automated language analysis of unnoticed and unresolved safety incidents

Safety reporting systems are widely used in healthcare to identify risks to patient safety. But, their effectiveness is undermined if staff do not notice or report incidents. Patients, however, might observe and report these overlooked incidents because they experience the consequences, are highly motivated, and independent of the organization. Online patient feedback may be especially valuable because it is a channel of reporting that allows patients to report without fear of consequence (e.g., anonymously). Harnessing this potential is challenging because online feedback is unstructured and lacks demonstrable validity and added value. Accordingly, we developed an automated language analysis method for measuring the likelihood of patient-reported safety incidents in online patient feedback. Feedback from patients and families (n = 146,685, words = 22,191,427, years = 2013–2019) about acute NHS trusts (hospital conglomerates; n = 134) in England were analyzed. The automated measure had good precision (0.69) and excellent recall (0.98) in identifying incidents; was independent of staff-reported incidents (r = −0.04 to 0.19); and was associated with hospital-level mortality rates (z = 3.87; p < 0.001). The identified safety incidents were often reported as unnoticed (89%) or unresolved (21%), suggesting that patients use online platforms to give visibility to safety concerns they believe have been missed or ignored. Online stakeholder feedback is akin to a safety valve; being independent and unconstrained it provides an outlet for reporting safety issues that may have been unnoticed or unresolved within formal channels.     

Measuring Knowledge,Attitudes and Behaviours Concerning Sustainable Development among Tenth Grade Students in Manitoba

In this paper we present standardized measures of tenth grade students’ knowledge, attitudes and behaviours concerning sustainable development as those concepts are understood in the United Nations Educational, Scientific and Cultural Organization, and we test the hypothesis that knowledge and favourable attitudes toward SD lead to favourable behaviours. Using a fairly representative random sample of 1,551 tenth grade students from the province of Manitoba, Canada, we crafted 3 indexes. There is a 20-item Index of Knowledge of SD with a good Cronbach alpha = 0.89, a 15-item Index of Attitudes Favourable Toward SD with alpha = 0.84 and a 15-item Index of Behaviours Favourable Toward SD with an alpha = 0.83. About 21% of the variation in our Behaviours Index scores could be accounted for by our Knowledge Index and Attitudes Index scores.     

Good Health is Not the Same as a Good Life: Survey Results from Brandon,Manitoba

The aim of this investigation was to obtain some baseline self-reported data on the health status and overall quality of life of a sample of residents of the city of Brandon, Manitoba aged 18 years or older, and to measure the impact of a set of designated health determinants, comparison standards and satisfaction with diverse domains of life on their health and quality of life. In May and June 2010, 2,500 households from the city of Brandon, Manitoba were randomly selected to receive a mailed out questionnaire and 518 useable, completed questionnaires were returned. Baseline health status data were obtained using the 8 SF-36 dimensions of health and 13 items from the United States Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System. Determinants of health and overall quality of life included measures of socializing activities, a Good Neighbourhood Index, Social Support Index, Community Health Index, a measure of free-time exercise levels, health-related behaviours, use of drugs, health care issues, a set of domain-specific quality of life items, a set of measures concerning criminal victimization, worries and behaviours concerning victimization and the basic postulates of Multiple Discrepancies Theory. Overall life assessment, dependent variables included Average Health, happiness, a single item measure of satisfaction with life as a whole, a single item measure of satisfaction with the overall quality of life, the Satisfaction With Life Scale, Contentment with Life Assessment Scale and a Subjective Wellbeing Index. Using multiple regression, we explained as much as 75% of the variance in Subjective Wellbeing scores and as little as 45% in happiness scores. Four clusters of health determinants explained from 20% (Happiness) to 44% (Average Health) of the variance in the dependent variables. Adding comparison standards and domain satisfaction scores to the set of health determinants increased our total explanatory power by only 2% points for Average Health (from 44 to 46%), but more than doubled our explanatory power for Happiness (from 20 to 45%) and for satisfaction with the overall quality of life (from 31 to 67%). As well, our explanatory power for the single item of Life Satisfaction increased from 34 to 66%, for the Satisfaction With Life Scale from 39 to 74%, for the Contentment With Life Assessment Scale from 36 to 60%, and for Subjective Wellbeing from 42 to 75%. This provided very clear evidence that self-perceived good health is not equivalent to perceived quality of life, confirming evidence reported in our earlier studies. The three most important take-home messages from this investigation are (1) in assessing the relative influence of any alleged determinants of health and the quality of life, different sets of alleged determinants will appear to be more or less influential for different dependent variables. Therefore, (2) researchers should use diverse sets of determinants and dependent variables and (3) it is a big mistake to use measures of health status as if they were measures of the perceived quality of life.     

A joint model of cancer incidence,metastasis, and mortality

Many diseases, especially cancer, are not static, but rather can be summarized by a series of events or stages (e.g. diagnosis, remission, recurrence, metastasis, death). Most available methods to analyze multi-stage data ignore intermediate events and focus on the terminal event or consider (time to) multiple events as independent. Competing-risk or semi-competing-risk models are often deficient in describing the complex relationship between disease progression events which are driven by a shared progression stochastic process. A multi-stage model can only examine two stages at a time and thus fails to capture the effect of one stage on the time spent between other stages. Moreover, most models do not account for latent stages. We propose a semi-parametric joint model of diagnosis, latent metastasis, and cancer death and use nonparametric maximum likelihood to estimate covariate effects on the risks of intermediate events and death and the dependence between them. We illustrate the model with Monte Carlo simulations and analysis of real data on prostate cancer from the SEER database.