Applications and Implementation A SEPARABLE PROGRAMMING APPROACH TO EXPECTED COVERAGE: AN APPLICATION TO AMBULANCE LOCATION

The maximum expected covering location problem (MEXCLP) is reformulated using a separable programming approach. The resulting formulation—nonlinear maximum expected covering location problem (NMEXCLP)—guarantees optimality and also solves more quickly than previous heuristic approaches. NMEXCLP allows two important extensions. First, minor formulation changes allow the specification of the minimum number of times each node is to be covered in order to satisfy expected coverage criteria. Second, coverage matrices can be constructed that consider two different types of coverage simultaneously. Both extensions are useful for ambulance location problems and are demonstrated in that setting.     

AN APPROXIMATION TO THE HYPERCUBE MODEL WITH PATROL-INITIATED ACTIVITIES: AN APPLICATION TO POLICE

This paper applies the patrol-initiated-activity hypercube queuing model to historical data from a police agency. The model allows servers to handle both calls assigned by a central dispatcher and activities initiated by the servers. By duplicating a fairly complex dispatch strategy, the model was found to predict both assigned and server-initiated work loads accurately for the overall system and individual servers. The model is apparently ineffective in predicting small unit-travel-time differences for this police agency.     

Guest editorial: Image analysis

Statistics and Computing -     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Self-Stigma of seeking help and job burnout in mental health care providers: the comparative study of Lithuanian and the USA samples

This study aimed to explore the correlation between job burnout and self-stigma of seeking help among nonmedical mental health care providers (psychologists, social workers, and counselors) in two countries – Lithuania and the US. The study included 234 professionals (111 social workers and 123 psychologists) from Lithuania and 93 professionals (33 counselors, 23 social workers, and 37 psychologists) from the US on a voluntary basis (93% females, mean age – 39.81?years). They completed a self-reported questionnaire with the Self-Stigma of Seeking Help Scale (SSOSH) and the Maslach Burnout Inventory-General Survey (MBI-GS). The results revealed a statistically significant positive correlation between self-stigmatization and burnout in the Lithuanian sample, but only weak positive correlation between depersonalization and self-stigma of seeking help in the US sample. The relationship between the self-stigma of seeking help and burnout was stronger in the Lithuanian sample of professionals when compared to their colleagues in the US.     

Predatory purchasing practices in global apparel supply chains and the employment relations squeeze in the Indian garment export industry

While the literature has long acknowledged worker rights abuses in global apparel supply chains, less attention has been paid to the recent worsening of certain decent work deficits and its causes, which this article links to predatory purchasing practices arising from growing power asymmetries. These practices, illustrated here by the garment export industry in India, exert downward pressure on wages and incite non‐standard forms of employment and greater verbal and physical abuse as productivity demands rise. They can be addressed through pricing mechanisms that cover the cost of decent work, appropriate State regulation and worker involvement.     

Betting is Loving and Bettors are Predators: A Conceptual Metaphor Approach to Online Sports Betting Advertising

The legalisation of online gambling in multiple territories has caused a growth in the exposure of consumers to online sports betting (OSB) advertising. While some efforts have been made to understand the visible structure of betting promotional messages, little is known about the latent components of OSB advertisements. The present study sought to address this issue by examining the metaphorical conceptualisation of OSB advertising. A sample of Spanish and British television OSB advertisements from 2014 to 2016 was analysed (N = 133). Following Lakoff and Johnson’s conceptual metaphor theory, four main structural metaphors that shaped how OSB advertising can be understood were identified: betting as (1) an act of love, (2) a market, (3) a sport, and (4) a natural environment. In general, these metaphors, which were found widely across 29 different betting brands, facilitated the perception of bettors as active players, with an executive role in the sport events bet upon, and greater control over bet outcomes.     

Cross Validation of the Gambling Problem Severity Subscale of the Canadian Adolescent Gambling Index (CAGI/GPSS) on a Sample of Ontario High School Students

This paper reports on the cross validation of the Gambling Problem Severity Subscale of the Canadian Adolescent Gambling Index (CAGI/GPSS). The CAGI/GPSS was included in a large school based drug use and health survey conducted in 2015. Data from students in grades 9–12 (ages 13–20 years) derived from the (N = 3369 students). The CAGI/GPSS produced an alpha of 0.789. A principle component analysis revealed two eigenvalues greater than one. An oblique rotation revealed these components to represent consequences and over involvement. The CAGI/GPSS indicated that 1% of the students fell into the “red” category indicating a severe problem and an additional 3.3% scored in the “yellow” category indicating low to moderate problems. The CAGI/GPSS was shown to be significantly correlated with gambling frequency (r = 0.36), largest expenditure (r = 0.37), sex (more likely to be male) (r = ?0.19), lower school marks (r = ?0.07), hazardous drinking, (r = 0.16), problem video game play (r = 0.16), as well as substance abuse. The CAGI/GPSS was cross validated using a shorted version of the short SOGS, r = 0.48. In addition the CAGI/GPSS and short SOGS produced very similar patterns of correlations results. The results support the validity and reliability of the CAGI/GPSS as a measure of gambling problems among adolescents.