Young people’s disillusionment with French education before 1968: sport,the school curriculum and social change

The quasi-revolutionary events of May 1968 have come to symbolize the generation gap between young people and their elders in France, and of contestation over social values, freedom and control. This article demonstrates that this discontent was apparent earlier in the decade, although politicians in charge of youth affairs either did not see it or chose not to publicize its existence. It focuses on debates relating to sport – and its incorporation into the teaching of physical education in lycées – because of its importance both within formal schooling and as an extra-curricular leisure activity. In 1966 François Missoffe, Minister of Youth Affairs and Sport, launched a huge inquiry into the problems facing young people, leading to the publication of an official report in 1967 which, perhaps surprisingly, had nothing to say about unrest among young people. This article aims to access the voices of young people in French lycées by mining the contents of over 2600 files of evidence that were collected during the course of the Missoffe inquiry. We argue that it is important to measure the gap between what the political and educational decision-makers presupposed about the sporting needs of young people and the views these same young people actually expressed. The article highlights examples of young people’s disillusionment with the teaching of sport and physical education, demonstrating that this not only conveyed signs of discontent with educational institutions as a whole but also a wider desire for social change that anticipated the views of angry lycéens (school pupils) in May 1968.     

Bayes prediction based on right censored data

This paper is concerned with a Bayes prediction problem in the exponential distribution under random censorship. Using censored samples, we work out a prediction interval for a sum of interest which consists of some future samples. Differing from the general Bayes approach, we do not specify the prior distribution of the parameter, and only a first moment condition on the prior is assumed. Simulation studies are conducted to exhibit the coverage probabilities of the prediction interval. Financial support from the IAP research network (#P5/24) of the Belgian Government (Belgian Science Policy) is gratefully acknowledged.     

Bequest motives and barriers to giving: The case of direct mail donors

Charitable bequests currently account for 9 percent of overall giving in the United States. In this study we examine the motives for this form of support and the potential barriers to giving perceived by members of bequest societies or legacy clubs solicited through direct mail. Through a series of eight focus groups we delineate the individual motives for offering a bequest, the organizational factors that drive gifts of this type, and the potential barriers that could prevent such a gift from being made. The implications for professional fundraising practice are explored.     

Estimation of a Copula when a Covariate Affects only Marginal Distributions

This paper is concerned with studying the dependence structure between two random variables Y₁ and Y₂ in the presence of a covariate X, which affects both marginal distributions but not the dependence structure. This is reflected in the property that the conditional copula of Y₁ and Y₂ given X, does not depend on the value of X. This latter independence often appears as a simplifying assumption in pair‐copula constructions. We introduce a general estimator for the copula in this specific setting and establish its consistency. Moreover, we consider some special cases, such as parametric or nonparametric location‐scale models for the effect of the covariate X on the marginals of Y₁ and Y₂ and show that in these cases, weak convergence of the estimator, at ‐rate, holds. The theoretical results are illustrated by simulations and a real data example.     

Uniform strong convergence results for the conditional kaplan-meier estimator and its quantiles

We consider a fixed design model in which the responses are possibly right censored. The aim of this paper is to establish some important almost sure convergence properties of the Kaplan-Meier type estimator for the lifetime distribution at a given covariate value. We also consider the corresponding quantile estimator and obtain a modulus of continuity result. Our rates of uniform strong convergence are obtained via exponential probability bounds.     

A relaxed approach to combinatorial problems in robustness and diagnostics

A range of procedures in both robustness and diagnostics require optimisation of a target functional over all subsamples of given size. Whereas such combinatorial problems are extremely difficult to solve exactly, something less than the global optimum can be ‘good enough’ for many practical purposes, as shown by example. Again, a relaxation strategy embeds these discrete, high-dimensional problems in continuous, low-dimensional ones. Overall, nonlinear optimisation methods can be exploited to provide a single, reasonably fast algorithm to handle a wide variety of problems of this kind, thereby providing a certain unity. Four running examples illustrate the approach. On the robustness side, algorithmic approximations to minimum covariance determinant (MCD) and least trimmed squares (LTS) estimation. And, on the diagnostic side, detection of multiple multivariate outliers and global diagnostic use of the likelihood displacement function. This last is developed here as a global complement to Cook’s (in J. R. Stat. Soc. 48:133–169, 1986) local analysis. Appropriate convergence of each branch of the algorithm is guaranteed for any target functional whose relaxed form is—in a natural generalisation of concavity, introduced here—‘gravitational’. Again, its descent strategy can downweight to zero contaminating cases in the starting position. A simulation study shows that, although not optimised for the LTS problem, our general algorithm holds its own with algorithms that are so optimised. An adapted algorithm relaxes the gravitational condition itself.     

Comparison of Kernel Density Estimators with Assumption on Number of Modes

A data-driven bandwidth choice for a kernel density estimator called critical bandwidth is investigated. This procedure allows the estimation to have as many modes as assumed for the density to estimate. Both Gaussian and uniform kernels are considered. For the Gaussian kernel, asymptotic results are given. For the uniform kernel, an argument against these properties is mentioned. These theoretical results are illustrated with a simulation study that compares the kernel estimators that rely on critical bandwidth with another one that uses a plug-in method to select its bandwidth. An estimator that consists in estimates of density contour clusters and takes assumptions on number of modes into account is also considered. Finally, the methodology is illustrated using environment monitoring data.