Additive Regression Model for Continuous Time Processes

In the setting of additive regression model for continuous time process, we establish the optimal uniform convergence rates and optimal asymptotic quadratic error of additive regression. To build our estimate, we use the marginal integration method.     

Social Class and Conversion Capacity: Deprivation Trends in the Great Recession in Ireland

In this paper, we draw on Irish SILC data to examine the roles of social class, non-class risk groups and state policies in influencing enforced material deprivation as Ireland moved from a period of economic boom through deep recession and on to early recovery. We also employ Sen’s capability approach to explore the extent to which certain social risk groups differ in their capacity to convert social class-differentiated resources into increased capability in relation to avoiding material deprivation. The findings refute the notion of polarization either across time as a result of recession or as a result of more vulnerable social risk groups experiencing more pronounced social class differences. Instead, the impact of recession on social class and social risk group operated mainly in an additive manner with each having a relatively independent impact on deprivation. The exception was lone parents who were less able to convert the benefits of higher social class position into reduced deprivation levels.     

Asymptotic normality of the posterior given a statistic

The authors establish the asymptotic normality and determine the limiting variance of the posterior density for a multivariate parameter, given the value of a consistent and asymptotically Gaussian statistic satisfying a uniform local central limit theorem. Their proof is given in the continuous case but generalizes to lattice‐valued random variables. It hinges on a uniform Edgeworth expansion used to control the behaviour of the conditioning statistic. They provide examples and show how their result can help in identifying reference priors.     

Latin hypercube sampling with inequality constraints

In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algorithm to build a Latin hypercube sample (LHS) taking into account inequality constraints between the sampled variables. This technique, called constrained Latin hypercube sampling (cLHS), consists in doing permutations on an initial LHS to honor the desired monotonic constraints. The relevance of this approach is shown on a real example concerning the numerical welding simulation, where the inequality constraints are caused by the physical decreasing of some material properties in function of the temperature.     

Social class variation in risk: a comparative analysis of the dynamics of economic vulnerability1

A joint concern with multidimensionality and dynamics is a defining feature of the pervasive use of the terminology of social exclusion in the European Union. The notion of social exclusion focuses attention on economic vulnerability in the sense of exposure to risk and uncertainty. Sociological concern with these issues has been associated with the thesis that risk and uncertainty have become more pervasive and extend substantially beyond the working class. This paper combines features of recent approaches to statistical modelling of poverty dynamics and multidimensional deprivation in order to develop our understanding of the dynamics of economic vulnerability. An analysis involving nine countries and covering the first five waves of the European Community Household Panel shows that, across nations and time, it is possible to identify an economically vulnerable class. This class is characterized by heightened risk of falling below a critical resource level, exposure to material deprivation and experience of subjective economic stress. Cross‐national differentials in persistence of vulnerability are wider than in the case of income poverty and less affected by measurement error. Economic vulnerability profiles vary across welfare regimes in a manner broadly consistent with our expectations. Variation in the impact of social class within and across countries provides no support for the argument that its role in structuring such risk has become much less important. Our findings suggest that it is possible to accept the importance of the emergence of new forms of social risk and acknowledge the significance of efforts to develop welfare states policies involving a shift of opportunities and decision making on to individuals without accepting the ‘death of social class’ thesis.     

Troubled Pastures,Troubled Pictures: French Agriculture and Contemporary Rural Sociology

Abstract In contrast to those of other industrialized western European countries, France's agricultural community continued to represent the majority of the national population for a long time and only became one of many minority groups at the end of the twentieth century. It then came under the influence of various trends, sometimes conflicting but nevertheless presenting a certain sociological and political unity. With the weakening of the demographic, territorial, economic, and political foundations of the French agricultural population, rural sociologists are now required to present a new analysis and a revised assessment of its position in French society. The object of this article is to promote better understanding of the reasons behind the blurring of images and representations associated with French agriculture. It invites readers to review and understand the different facets of an imagery that presents a paradox compared with the ideological constructs associated with the historical record of farming and the farming profession. Working in the tradition of the French school of rural sociology, we have set out to offer a sense of the social realities that now represent the main areas of analysis for French and European rural sociology.     

Youth Participatory Action Research Findings as Mirror Material: Implications for Advancing Educational Equity Through Formative Interventions

Formative intervention research holds potential as a tool to disrupt systemic racism and advance equity in education. However, one aspect of formative interventions could be an impediment to realizing this potential, specifically the “mirror material”: data collected by outside researchers meant to provide participants a starting point to co-construct an understanding of a problem. Focusing on mirror material, this article draws insights from a youth participatory action research group to question whose knowledge should provide the grounding for formative interventions. Ultimately, we contend that youth of color should be involved in generating mirror material in equity-oriented formative interventions in education.     

A Decision Support Tool to Compare Waterborne and Foodborne Infection and/or Illness Risks Associated with Climate Change

Climate change may impact waterborne and foodborne infectious disease, but to what extent is uncertain. Estimating climate‐change‐associated relative infection risks from exposure to viruses, bacteria, or parasites in water or food is critical for guiding adaptation measures. We present a computational tool for strategic decision making that describes the behavior of pathogens using location‐specific input data under current and projected climate conditions. Pathogen‐pathway combinations are available for exposure to norovirus, Campylobacter, Cryptosporidium, and noncholera Vibrio species via drinking water, bathing water, oysters, or chicken fillets. Infection risk outcomes generated by the tool under current climate conditions correspond with those published in the literature. The tool demonstrates that increasing temperatures lead to increasing risks for infection with Campylobacter from consuming raw/undercooked chicken fillet and for Vibrio from water exposure. Increasing frequencies of drought generally lead to an elevated infection risk of exposure to persistent pathogens such as norovirus and Cryptosporidium, but decreasing risk of exposure to rapidly inactivating pathogens, like Campylobacter. The opposite is the case with increasing annual precipitation; an upsurge of heavy rainfall events leads to more peaks in infection risks in all cases. The interdisciplinary tool presented here can be used to guide climate change adaptation strategies focused on infectious diseases.