Is Social Innovation Fostering Satisfaction and Well-Being at Work? Insights from Employment in Social Enterprises Providing Long-Term Eldercare Services

Considering insights from socio-economics, work psychology, and occupational health, this study focuses on the job satisfaction and well-being of employees working in nonprofit social enterprises (SE). We question the idea suggested by the recent literature that working for a SE brings employees a high level of job satisfaction and well-being. We also investigate whether being involved in social innovation is associated with even higher job satisfaction and well-being. Indeed, understood as a manifestation of positive social change, social innovation is expected to improve outcomes such as the quality of life at work. However, because social innovation is an umbrella concept, it embraces different innovation-related concepts. Here we explore the distinction between service innovation and workplace innovation. This article applies a multivariate analysis to an original dataset covering 1134 employees working in the field of elder homecare in Wallonia. Its implications for social entrepreneurs and scholars are also examined.     

Robust nonparametric estimation for spatial regression

In this paper, we investigate a nonparametric robust estimation for spatial regression. More precisely, given a strictly stationary random field _Zi=(_Xi,_{Yi)i∈NNN≥1}$Z_{\mathbf{i}}=(X_{\mathbf{i}},Y_{\mathbf{i}}{)}_{\mathbf{i}\in {\mathbb{N}}^{N}N\ge 1}$, we consider a family of robust nonparametric estimators for a regression function based on the kernel method. Under some general mixing assumptions, the almost complete consistency and the asymptotic normality of these estimators are obtained. A robust procedure to select the smoothing parameter adapted to the spatial data is also discussed.     

A Fast Iterated Bootstrap Procedure for Approximating the Small-Sample Bias

This article proposes a fast approximation for the small sample bias correction of the iterated bootstrap. The approximation adapts existing fast approximation techniques of the bootstrap p-value and quantile functions to the problem of estimating the bias function. We show an optimality result which holds under general conditions not requiring an asymptotic pivot. Monte Carlo evidence, from the linear instrumental variable model and the nonlinear GMM, suggest that in addition to its computational appeal and success in reducing the mean and median bias in identified models, the fast approximation provides scope for bias reduction in weakly identified configurations.     

What About a Sociology of Ethnicity in France? A Foucaldian Reading of Racial Violence

In 1995, the publication of “Theories of ethnicity” by Philippe Poutignat and Jocelyne Streiff-Fenart pointed out the new interest of French sociology for this theme. Since that time, the number of research about ethnicity has been gradually increasing. Yet, certain questions remain unsettled. In France, sociology of ethnicity does not constitute a full-fledged field. In parallel, ethnicity works are still inspired by Anglo-Saxon research. Eventually, contrary to what happened in the United States, sociologists did not draw on the Foucaldian library to nourish close and relevant fields such as subaltern or postcolonial studies. On the basis of a research regarding the immigration policy and the racial violence perpetrated against North African migrants in France during the 1970s, this article adopts a critical perspective with the aim to restore the failed dialogue in France between the Foucaldian analysis of State racism and the study of ethnicity.