Engaging Expert Peers in the Development of Risk Assessments

The participation of external technical experts in the development of risk assessment documents and methodologies has expanded and evolved in recent years. Many government agencies and authoritative organizations have experts peer review important works to evaluate the scientific and technical defensibility and judge the strength of the assumptions and conclusions (OMB, 2004; IPCS, 2005; IARC, 2006; Health Canada, 2007; U.S. EPA, 2006). Expert advice has been solicited in other forms of peer involvement, including peer consultation in, for example, the U.S. EPA's Voluntary Children's Chemical Evaluation Program (VCCEP). This article discusses how the principles and practices of peer review can be extended to other types of peer involvement activities (i.e., peer input and peer consultation) to develop high-quality risk assessment work products. A comprehensive process for incorporating peer input, peer consultation, and peer review into risk assessment science is outlined. Four key principles for peer involvement-independence, inclusion of appropriate experts, transparency, and a robust scientific process-are discussed. Recent examples of peer involvement in the development of Health Canada's Priority Substances and Domestic Substance List (DSL) programs under the Canadian Environmental Protection Act (CEPA) serve to highlight the concepts.     

Comparison of Six Dose-Response Models for Use with Food-Borne Pathogens

Food-related illness in the United States is estimated to affect over six million people per year and cost the economy several billion dollars. These illnesses and costs could be reduced if minimum infectious doses were established and used as the basis of regulations and monitoring. However, standard methodologies for dose-response assessment are not yet formulated for microbial risk assessment. The objective of this study was to compare dose-response models for food-borne pathogens and determine which models were most appropriate for a range of pathogens. The statistical models proposed in the literature and chosen for comparison purposes were log-normal, log-logistic, exponential, -Poisson and Weibull-Gamma. These were fit to four data sets also taken from published literature, Shigella flexneri, Shigella dysenteriae,Campylobacter jejuni, and Salmonella typhosa, using the method of maximum likelihood. The Weibull-gamma, the only model with three parameters, was also the only model capable of fitting all the data sets examined using the maximum likelihood estimation for comparisons. Infectious doses were also calculated using each model. Within any given data set, the infectious dose estimated to affect one percent of the population ranged from one order of magnitude to as much as nine orders of magnitude, illustrating the differences in extrapolation of the dose response models. More data are needed to compare models and examine extrapolation from high to low doses for food-borne pathogens.     

Combining Probability Distributions From Experts in Risk Analysis

This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual and practical issues to be considered in designing a combination process in practice. The role of experts is important because their judgments can provide valuable information, particularly in view of the limited availability of hard data regarding many important uncertainties in risk analysis. Because uncertainties are represented in terms of probability distributions in probabilistic risk analysis (PRA), we consider expert information in terms of probability distributions. The motivation for the use of multiple experts is simply the desire to obtain as much information as possible. Combining experts' probability distributions summarizes the accumulated information for risk analysts and decision-makers. Procedures for combining probability distributions are often compartmentalized as mathematical aggregation methods or behavioral approaches, and we discuss both categories. However, an overall aggregation process could involve both mathematical and behavioral aspects, and no single process is best in all circumstances. An understanding of the pros and cons of different methods and the key issues to consider is valuable in the design of a combination process for a specific PRA. The output, a combined probability distribution, can ideally be viewed as representing a summary of the current state of expert opinion regarding the uncertainty of interest.     

The Effects of Learning,Forgetting, and Relearning on Decision Rule Performance in Multiproject Scheduling

Product development occurs in multiproject environments where preemption is often allowed so that critical projects can be addressed immediately. Because product development is characterized by time-based competition, there is pressure to make decisions quickly using heuristics methods that yield fast project completion. Preemption heuristics are needed both to choose activities for preemption and then to determine which resources to use to restart preempted activities. Past research involving preemption has ignored any completion time penalty due to the forgetting experienced by project personnel during preemption and the resulting relearning time required to regain lost proficiency. The purpose of this research is to determine the impact of learning, forgetting, and relearning (LFR) on project completion time when preemption is allowed. We present a model for the LFR cycle in multiproject development environments. We test a number of priority rules for activity scheduling, activity preemption, and resource assignment subsequent to preemption, subject to the existence of the LFR cycle, for which a single type of knowledge worker resource is assigned among multiple projects. The results of the simulation experiments clearly demonstrate that LFR effects are significant. The tests of different scheduling, preemption, and resource reassignment rules show that the choice of rule is crucial in mitigating the completion time penalty effects of the LFR cycle, while maintaining high levels of resource utilization. Specifically, the worst performing rules tested for each performance measure are those that attempt to maintain high resource utilization. The best performing rules are based on activity criticality and resource learning.     

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.     

The religious and worldview dimension of intercultural education: the Council of Europe’s contribution

ABSTRACT

This article traces the Council of Europe’s work on teaching about religions and non-religious worldviews, regarded as an important contributor to intercultural education. It explains why studies of religions came late in the Council of Europe’s educational work and traces the development of a project which led to a Recommendation from its Committee of Ministers on teaching about religions and non-religious worldviews. It summarises follow-up work by the Council of Europe and the European Wergeland Centre, which led to the publication of Signposts. It outlines new research on themes identified in Signposts and discusses the relationship between intercultural education and studies of religions, in the context of the Council of Europe and responds to criticisms of its work. An account of the development of a new teacher training module, based on Signposts, is given. The module can be adapted for use in Council of Europe member states and in different settings, including university and school-based teacher training. An account is given of the work of the module’s writing group, its structure and chapters, the piloting undertaken and how it could develop. Finally, this article introduces the concept of ‘dialogical liberalism’, aiming to promote dialogue and discussion, rather than imposing equality.