Nonparametric Bayesian Methods for Benchmark Dose Estimation

The article proposes and investigates the performance of two Bayesian nonparametric estimation procedures in the context of benchmark dose estimation in toxicological animal experiments. The methodology is illustrated using several existing animal dose‐response data sets and is compared with traditional parametric methods available in standard benchmark dose estimation software (BMDS), as well as with a published model‐averaging approach and a frequentist nonparametric approach. These comparisons together with simulation studies suggest that the nonparametric methods provide a lot of flexibility in terms of model fit and can be a very useful tool in benchmark dose estimation studies, especially when standard parametric models fail to fit to the data adequately.     

The Intuitive Detection Theorist (IDT) Model of Trust in Hazard Managers

The intuitive detection theorist (IDT) model of trust posits that trust in hazard managers stems from judgments about their performance on three criteria: their ability to discriminate safe from dangerous situations (discrimination ability); their tendency under uncertainty to assume danger is present (response bias); and their propensity to be open and honest with the public about events (communication bias). The current article tests the model's robustness using findings from three experiments and four surveys conducted by two different research teams. Study‐specific analyses and an overall analysis of the seven studies combined confirm that all three of the IDT model's dimensions are important for trust, explaining on average 43% of trust variance. These effects occurred largely independently of hazard topic, research method, or investigator. Hypothesized interaction effects among the dimensions, based upon earlier studies, were weak and contradictory; this is the first known study of interactions among trust model variables.     

A performance measurement paradigm for integrating strategy formulation: A review of systems and frameworks

Measuring organizational performance plays a very important part in translating corporate strategy into results. Various emerging (non-traditional) performance systems have recently been devised to aid firms in selecting and implementing measures. This paper discusses the strategy/measurement initiatives and compares ten emerging performance measurement systems with respect to a list of performance dimensions, the characteristics of performance measures, and the requirements of development process. Although these systems have constraints borne with their own application domains, they stand by themselves empirically and/or theoretically, and provide guidance about what to measure and how to design performance measures that could be linked to the corporate strategy and objectives of an organization. This paper concludes that there is a need to develop a paradigm for integrating strategy formulation and performance measurement in organizations.     

A FISCAL THEORY OF GOVERNMENT'S ROLE IN MONEY

As an alternative to market failure explanations, we draw on theory and historical evidence to argue that fiscal considerations explain the roles governments typically play in producing and regulating money. Public monopoly production of coins and banknotes, substitution offiat for commodity standards, and restrictions on substitutes for government money all generate revenue and especially provide means for meeting fiscal emergencies. We argue that these arrangements do not reflect conscious design so much as the evolutionary survival of the fiscally advantageous. ( JEL E5, E6, H1, N1)     

Nowhere to go: Housing pathways of college students with foster care and homelessness experience

This study builds on previous research to understand longer term housing experiences in late adolescence and early adulthood for vulnerable college students. Using a biographical, qualitative method, we study high school and college housing and family circumstances for 27 students with homelessness or foster care experience enrolled in 4-year colleges in Georgia. We identified three different housing pathway types in high school—family homelessness, unaccompanied youth and foster care. Housing instability and frequent moves were common in high school among all housing pathway types. In college, students who were able to find low or no-cost housing and those who identified a foster care pathway in high school achieved greater housing stability. Others students experienced a continuation of housing instability that began in high school. Additional funding to cover the cost of on-campus housing would likely contribute to increased stability. Additional strategies, such as rental assistance programmes tailored for college students, may be needed to address housing instability for vulnerable college students. More research on the unmet housing needs and the consequences of housing instability during college for homeless and foster youth is needed to further a housing policy agenda that focuses on practical solutions.     

Nano Risk Analysis: Advancing the Science for Nanomaterials Risk Management

Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.     

Risk Characterization for Nanotechnology

Nanotechnology is a broad term that encompasses materials, structures, or processes that utilize engineered nanomaterials, which can be defined as materials intentionally designed to have one or more dimensions between 1 and 100 nm. Historically, risk characterization has been viewed as the final phase of a risk assessment process that integrates hazard identification, dose‐response assessment, and exposure assessment. The novelty and diversity of materials, structures, and tools that are covered by above‐defined “nanotechnology” raise substantial methodological issues and pose significant challenges for each of these phases of risk assessment. These issues and challenges culminate in the risk characterization phase of the risk assessment process, and this article discusses several of these key issues and approaches to developing risk characterization results and their implications for risk management decision making that are specific to nanotechnology.     

Trust among recent immigrants in Canada: levels,roots and implications for immigrant integration

ABSTRACT

Generalised trust promotes social interactions and may well be a crucial component of immigrant integration. Recent immigrants in particular are likely to be viewed by themselves and others as ‘outsiders’ who are unfamiliar with the expectations and norms that structure day-to-day social interactions in the host country. This study relies on a unique combination of three sources of data all derived from World Values Surveys to examine levels of trust, and its sources, among newcomers in one country with a large immigrant population, Canada. The evidence indicates that recent immigrants to Canada make a clear distinction between trust in other people in general, and trust in Canadians in particular: the former is grounded in pre-migration cultural influences, while the latter is grounded in immigrants’ experiences in the new host country. Moreover, the evidence suggests trust in Canadians is a crucial component of immigrant integration.     

The Effect of Integrated Scheduling and Capacity Policies on Clinical Efficiency

In outpatient healthcare clinics, capacity, patient flow, and scheduling are rarely managed in an integrated fashion, so a question of interest is whether clinic performance can be improved if the policies that guide these decisions are set jointly. Despite the potential importance of this issue, we find surprisingly few studies that look at how the allocation of capacity, paired with various appointment scheduling policies and different patient flow configurations, affects patient flow and clinical efficiency. In this paper, we develop an empirically based discrete‐event simulation to examine the interactions between patient appointment policies and capacity allocation policies (i.e., the number of available examination rooms) and how they jointly affect various performance measures, such as resource utilization and patient waiting time. Findings suggest that scheduling lower‐variance, shorter appointments earlier in the clinic (and, conversely, higher‐variance, longer appointments later) results in less overall patient waiting without reducing physician utilization or increasing clinic duration. Additionally, exam rooms exhibited classic bottleneck behavior: there was no effect on physician utilization by adding exam rooms beyond a certain threshold, but too few exam rooms were devastating to clinic throughput. Some significant interactions between these variables were observed, but were not influential to the level of managerial concern. Clinicians' intuition about managing capacity in healthcare settings may differ substantially from best policies.