La production de la sécurité sanitaire au quotidien : l’inspection des services vétérinaires en abattoir

Slaughterhouses are a decisive link in a healthy food chain. Officials from veterinary services, stationed there full-time, work next to personnel on the line so that the food produced is safe for human consumption. Each inspector has to lay the grounds for his/her individual position of authority to exercise controls. This control also depends on ongoing exchanges among inspection team members and on their knowing the distance to keep from workers on the line. Recent food and health scares, along with reforms for modernizing interventions by public authorities, have made controls more formalistic. References to standards and procedures for carrying out interventions and filing reports have been thoroughly modified. This study in France of the switch from an educational approach to food inspection to a procedural one, wherein written texts have an unprecedented scope, focuses on the concrete implications for inspectors, especially in terms of human relations. Light is shed on how the possibility of legal action has shaped these changes.     

The poor,the rich and the happy: Exploring the link between income and subjective well-being

The relationship between income and subjective well-being (SWB) is investigated using eight waves of the British Household Panel Survey and an estimation strategy that allows us to relax some assumptions typically made in the literature. First, we use a random effects generalised ordered probit model to investigate whether income effects are heterogeneous across SWB categories, and, second, we discretise (absolute and relative) income variables to allow for the income effects to vary across income groups. We find that higher absolute income increases SWB but up to a certain level, while low income is significantly correlated with low scores in the SWB ladder. Our results are consistent with the Easterlin Paradox that has been reported in the literature. We find that high-income groups are less likely to belong in the highest SWB level, which could be partly explained by the fact that the relative income status (rather than the absolute one) is more important in determining (the highest level of) SWB.     

Cellular automata and Riccati equation models for diffusion of innovations

Innovation diffusion represents a central topic both for researchers and for managers and policy makers. Traditionally, it has been examined using the successful Bass models (BM, GBM), based on an aggregate differential approach, which assures flexibility and reliable forecasts. More recently, the rising interest towards adoptions at the individual level has suggested the use of agent based models, like Cellular Automata models (CA), that are generally implemented through computer simulations. In this paper we present a link between a particular kind of CA and a separable non autonomous Riccati equation, whose general structure includes the Bass models as a special case. Through this link we propose an alternative to direct computer simulations, based on real data, and a new aggregate model, which simultaneously considers birth and death processes within the diffusion. The main results, referred to the closed form solution, the identification and the statistical analysis of our new model, may be both of theoretical and empirical interest. In particular, we examine two applied case studies, illustrating some forecasting improvements obtained.     

Do depressive symptoms in justice‐involved girls reduce the effects of a cognitive‐behavioral program on their disruptive and delinquent behaviors?

The present study evaluated the effects of a cognitive‐behavioral program on disruptive and delinquent behaviors among a sample of adolescent girls placed in a residential center in Quebec (Canada). This study also investigated the moderating impact of depressive symptoms on program effectiveness. The study used a quasi‐experimental design to allow comparisons between 104 girls in the treatment group and 78 girls in the comparison group over 18 months. Findings showed that the program contributed significantly, albeit modestly, to a decline in some forms of disruptive/delinquent behaviors. Results also indicated that girls with a higher level of depressive symptoms at admission also reported higher involvement in a myriad of disruptive/delinquent behaviors and that for some types of problem behaviors, this higher involvement persisted over time. In general, however, the seriousness of the depressive symptoms that the girls reported at admission did not interfere with the effectiveness of the cognitive‐behavioral program.     

On the extremal behavior of a nonstationary normal random field

Let X={_Xn}n?1$\mathbf{X}=\{X_{\mathbf{n}}{\}}_{\mathbf{n}?\mathbf{1}}$ be a nonstationary random field satisfying a long range weak dependence for each coordinate at a time and a local dependence condition that avoids clustering of exceedances of high values. For these random fields, the probability of no exceedances of high values can be approximated by exp(−τ)$\exp (-\tau )$, where τ$\tau$ is the limiting mean number of exceedances. We present a class of nonstationary normal random fields for which this result can be applied.     

Scatter Plot and Additional Variables

We often want to complete the interpretation of the usual graphs (x, y) with additional quantitative variables. The Prefmap method (vectorial model) proposes a representation of these additional variables but this representation has some drawbacks when the variables x and y are correlated. To solve this problem, we propose to substitute the coefficients of the linear regression by the coefficient of the PLS regression in the Prefmap method. The graph obtained is made operational thanks to contour lines of quality of representation and it becomes richer than the Prefmap one.     

Restructuring Among the World's Leading Oil Companies, 1980–92

Restructuring among the international oil majors during 1980–92 involved simultaneous, system-wide changes in strategies and structures dictated by the demands of a more competitive, unstable business environment, but triggered by declining profitability and motivated by the desire to increase shareholder returns. Restructuring involved transition from one strategy-structure configuration, the 'administrative planning model', to another, the 'market responsiveness model'. The multiple strategic and structural changes were linked by a unifying theme: the quest for efficiency in a turbulent environment. This quest presented the companies with a strategic dilemma - reconciling economies of scale and scope with the benefits of flexibility; and a structural dilemma - reconciling decentralization with coordination. This paper draws upon the experiences of the world's eight largest international oil majors.     

On identifiability of parametric statistical models

Summary This is a review article on statistical identifiability. Besides the definition of the main concepts, we deal with several questions relevant to the statistician: parallelism between parametric identifiability and sample sufficiency; relationship of identifiability with measures of sample information and with the inferential concept of estimability; several strategies of making inferences in unidentifiable models with emphasis on the distinct behaviour of the classical and Bayesian approaches. The concepts, ideas and methods discussed are illustrated with simple examples of statistical models. Centro de Análise e Processamento de Sinais da UTL     

A class of residuals for outlier identification in zero adjusted regression models

Zero adjusted regression models are used to fit variables that are discrete at zero and continuous at some interval of the positive real numbers. Diagnostic analysis in these models is usually performed using the randomized quantile residual, which is useful for checking the overall adequacy of a zero adjusted regression model. However, it may fail to identify some outliers. In this work, we introduce a class of residuals for outlier identification in zero adjusted regression models. Monte Carlo simulation studies and two applications suggest that one of the residuals of the class introduced here has good properties and detects outliers that are not identified by the randomized quantile residual.