Sport and disability: Pistorius does not fit with the categories

Oscar Pistorius presents a major issue to sports organisations, as exposed in the media. First and foremost, media wrongly perceive him as the first disabled athlete to participate in the Olympic Games. Second, they openly question the legitimacy of his participation mainly based on the inequity introduced by his prosthetic legs. Content analysis, in English and French, of written press, International Association of Athletics Federations (IAAF) and Court of Arbitration for Sport (CAS) texts, from 2004 to 2012, confirms that Pistorius presents a new puzzle to sports organizations. This is partly because they are not able to determine whether his performances are a result of his body strength or if they are biased by his artificial limbs. Furthermore, when he is competing against able-bodied athletes, sports organizsations put him in a ‘monstrous’ position. Similarly, while categorising him as an ‘athlete’ they do not grant him the characteristic feature of this category: certified comparability of performances to ultimately establish ranks.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

The Impact of Macro- and Micro-Economic Uncertainty on Family Formation in The Netherlands

In this paper, we study the impact of macro- and micro-economic uncertainty on family formation between 1970 and 2000 in The Netherlands. Using data of the Family Survey Dutch Population, we analysed the monthly hazard rates of experiencing the transition into first union, first marriage and parenthood after the start of the relationship of 365 male and 364 female partners by applying piecewise-constant exponential models. The results show that macro-economic uncertainties, i.e. high unemployment rates, lead to postponement of the first union and marriage, but not of the first child. In addition, we found that this relationship is not interpreted by individual-level employment insecurity, i.e. temporary employment or unemployment, which does not seem to prevent people from making long-term family commitments. Although hypothesized, we did not find that the negative effects of macro- and micro-level insecurities on family formation reinforce each other or that they vary between individuals with different educational qualifications.     

Hallmarks of the Political in Community Organizing: An Arendtian Perspective

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Drawing upon Hannah Arendt’s adherence to existential phenomenology, the article advances a political understanding...     

State Immigration Policies: The Role of State Compacts and Interest Groups on Immigration Legislation

US states are active in enacting immigration policies, which vary widely and have substantial impact on the lives of immigrants. Our understanding of what produces these divergent state laws remains limited. Qualitative research demonstrates the importance of a 2010 immigration compact, supported by a powerful religious organization, in shaping immigration policies in Utah, and the Utah Compact was held up as a model for other states. But is the experience of Utah applicable across other states? We test the effects of compacts and interest groups on immigration policy adoption across all 50 states between 2005 and 2013. Our findings suggest that compacts are actually associated with more restrictive immigration policy. Although states with compacts are more likely to pass inclusive immigration laws, these are counterbalanced by higher numbers of exclusive laws. Both religious and non‐religious interests groups are associated with policy, but they do not explain the effects of compacts.     

Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes

The recently developed rolling year GEKS procedure makes maximum use of all matches in the data to construct nonrevisable price indexes that are approximately free from chain drift. A potential weakness is that unmatched items are ignored. In this article we use imputation Törnqvist price indexes as inputs into the rolling year GEKS procedure. These indexes account for quality changes by imputing the “missing prices” associated with new and disappearing items. Three imputation methods are discussed. The first method makes explicit imputations using a hedonic regression model which is estimated for each time period. The other two methods make implicit imputations; they are based on time dummy hedonic and time-product dummy regression models and are estimated on bilateral pooled data. We present empirical evidence for New Zealand from scanner data on eight consumer electronics products and find that accounting for quality change can make a substantial difference.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

The Decomposition of Economic Outcomes as a Result of Changes in Brazil’s Male Age–Education Structure

In Brazil, the age and education compositions of the male labor force is changing with great regional variation. Based on Demographic Census microdata, results indicate that cohort size has a negative impact on earnings, but this effect is decreasing over time. In this study we consider the impact on earnings by age and education, as well as estimated income inequality reduction and racial differentials. Fertility decline and improve regarding educational attainment had a significant influence on the decline of income inequality in the country. Moreover, the non-white population has been experiencing less success in relation to educational achievement, compared to the white population.