Virtually all indicators of physical health and mental competence favor persons of higher socioeconomic status (SES). Conventional theories in the social sciences assume that the material disadvantages of lower SES are primarily responsible for these inequalities, either directly or by inducing psychosocial harm. These theories cannot explain, however, why the relation between SES and health outcomes (knowledge, behavior, morbidity, and mortality) is not only remarkably general across time, place, disease, and kind of health system but also so finely graded up the entire SES continuum. Epidemiologists have therefore posited, but not yet identified, a more general "fundamental cause" of health inequalities. This article concatenates various bodies of evidence to demonstrate that differences in general intelligence (g) may be that fundamental cause.

/pdf/intelligence-is-it-the-epidemiologists-elusive-fundamental-22lkchbeke.pdf

Intelligence: Is It the Epidemiologists' Elusive "Fundamental Cause" of Social Class Inequalities in Health?

In this research we conducted a systematic reviewon Global Software Development (GSD) literature andperformed a survey to gather challenges associated with GSDprojects as well as their mitigation strategies. We reviewedstudies with empirical evidence in GSD. In total there are 86papers included as the primary studies. From the systematicreview we collected 48 challenges and 42 mitigation strategies.These challenges and strategies were also identified by our survey respondents. In addition, 4 additional mitigation strategies were uncovered from the survey. The collected challenges and mitigation strategies are later compiled into checklists which can be employed as risk identification and risk mitigation instruments.

/pdf/risk-identification-and-risk-mitigation-instruments-for-4huzgcrht6.pdf

Risk Identification and Risk Mitigation Instruments for Global Software Development: Systematic Review and Survey Results

Objectives This study examines the concept and measurement of worker's safety behavior. It shows that the traditional concept of safety behavior centered on workers' carefulness or compliance with safety rules is limited and proposes that an additional dimension, namely, workers' safety initiatives, be taken into account. Methods Confirmatory factor analyses were carried out for a random sample of 828 workers drawn from 9 manufacturing facilities located in the province of Quebec (Canada). Results A 2-correlated congeneric factor model gave parameters in the expected direction, but the overall model was unable to reach a good fit. Separate construct analyses showed that compliance with safety rules is not a consistent dimension. The safety-initiatives dimension achieved a good fit with a high composite reliability (r=0.85). Conclusion Workers' compliance with safety rules was not structured as a unitary dimension; therefore a selective process of safety-rules compliance by workers is suggested. Each category of safety rules should be considered as 1 single dimension and measured by several specific indicators. Indicators for safety initiatives provide high reliability, and, since this dimension is an important predictor of effectiveness in accident prevention, the items tested provide a better measurement than those previously published.

From a unidimensional to a bidimensional concept and measurement of workers' safety behavior

After a number of food safety crises, the design and implementation of traceability systems became an important tool for managing safety risks in the food industry. In the literature, numerous studies deal with traceability from the viewpoint of information system and technology development. However, traceability and its implications for food safety receive less attention in literature on production and distribution planning. From the viewpoint of operations management, an efficient management of food safety risks requires the consideration of the amounts of potentially recalled products, affected regions/customers, and logistics efforts connected to solving the safety problem. In this paper we are developing a production and distribution planning model for food supply chains to address these issues. We also present heuristics for solving the resulting mixed-integer linear programming model and demonstrate the effectiveness of the developed methodology in a numerical investigation.

A methodology for controlling dispersion in food production and distribution

The risk appetite concept has been given considerable attention recently in enterprise risk management contexts. A number of definitions exist, most with a link to risk acceptability, but also values and goals. The usefulness of the concept is, however, disputed; some authors argue that we can in fact do better without it. In this article, we provide a thorough discussion of what the risk appetite concept is actually trying to express and how it best can be used in the relevant decision making. The main purposes of the article are (i) to argue that the risk appetite concept, suitably interpreted, has a role to play in risk management, (ii) to show that the risk appetite concept is well supported by some types of risk perspectives and not by others, and (iii) to show how the risk appetite concept is linked to other related concepts, such as risk seeking and risk acceptability. The risk perspectives studied range from expected value and probability based definitions of risk to views on risk, that are founded on uncertainties.

On the meaning and use of the risk appetite concept.

Understanding and Managing Risk Attitude, by D. Hillson, and R. Murray-Webster, Gower, Aldershot, 2007 [2nd edition], pp.180, £25.00 (ISBN: 978-0-566-08798-1) This book is aimed at anyone involved ...

Understanding and Managing Risk Attitude

A review of: “Individual Behaviour in the Control of Danger.” By ANDREW R. HALE and A. IAN GLENDON. (Amsterdam: Elsevier, 1987.)

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Understanding and Managing Risk Attitude

A review of: “Individual Behaviour in the Control of Danger.” By ANDREW R. HALE and A. IAN GLENDON. (Amsterdam: Elsevier, 1987.)