Using job strain and organizational justice models to predict multiple forms of employee performance behaviours among Australian policing personnel

The overall purpose of this investigation was to examine the relationship between stress-related working conditions and three forms of employee performance behaviours: in-role behaviours, citizenship behaviours directed at other individuals and citizenship behaviours directed at the organization. The potentially stressful working conditions were based on the job strain model (incorporating job demands, job control and social support) as well as organizational justice theory. A sample of Australian-based police officers (n = 640) took part in this study and the data were collected via a mail-out survey. Multiple regression analyses were undertaken to assess both the strength and the nature of the relationships between the working conditions and employee performance and these analyses included tests for additive, interactional and curvilinear effects. The overall results indicated that a significant proportion of the explained variance in all three outcome measures was attributed to the additive effects of demand, control and support. The level of variance associated with the organizational justice dimensions was relatively small, although there were signs that specific dimensions of justice may provide unique insights into the relationship between job stressors and employee performance. The implications of these and other notable findings are discussed.

Robust modular artmap for multi-class shape recognition

This paper presents a fuzzy ARTMAP (FAM) based modular architecture for multi-class pattern recognition known as modular adaptive resonance theory map (MARTMAP). The prediction of class membership is made collectively by combining outputs from multiple novelty detectors. Distance-based familiarity discrimination is introduced to improve the robustness of MARTMAP in the presence of noise. The effectiveness of the proposed architecture is analyzed and compared with ARTMAP-FD network, FAM network, and One-Against-One Support Vector Machine (OAO-SVM). Experimental results show that MARTMAP is able to retain effective familiarity discrimination in noisy environment, and yet less sensitive to class imbalance problem as compared to its counterparts.

Global forms and local forces : PhD enrollments and graduations in Australia, Canada, the Czech Republic, the United Kingdom, and the United States

 This chapter presents and discusses data from five different nations—Australia, Canada, the Czech Republic, the United Kingdom, and the United States—on doctoral candidates and graduates. These data are from governmental and institutional sources for the years 1998–2004, a sample that enables changes across a five-year span to be identified. They span important basic characteristics, such as gender, age, discipline, and study load (that is, full-time or part-time study). Therefore, readers can see national as well as international trends and differences in such characteristics and can match these to equivalent and/or contemporary data in their own nations. The five countries considered here are among those whose data were discussed at the 2007 CIRGE research synthesis meeting in Australia. Although these countries are not universally representative of doctoral education, their practices do offer a vivid sense of how vastly the enterprise of doctoral education differs in its scope and dimensions around the world