The Media Abuse of Children. Jake's Progress from Demonic Icon to Restored Childhood Innocent

While scholarly analysis of child protection and the media has grown substantially during the 1990s (Aldridge, 1994; Franklin and Parton, 1991; Kitzinger and Skidmore, 1995), studies have ignored a crucial dimension which forms the focus for discussion here. We wish to suggest that media reporting of children and child abuse may itself constitute an abusive activity. Media presentations of children and childhood, since press coverage of the Bulger case in 1993, have assumed a distinctive and sinister guise which, we argue, fundamentally revises the previously held perception of children and childhood. We suggest that this new understanding of childhood is damaging to children and, because of the impact of such media presentations on the public mood and policy climate, harms their interests. The discussion is in three parts. First, newspaper reporting of the Bulger case is analysed to reveal how coverage challenged the idea of childhood as a period of innocence and replaced it with a perception of childhood as essentially ‘evil’. Second, the characterization of Jake, the central figure in Alan Bleasdale's recent television dramaJake's Progress, is analysed to serve as an illustrative exemplar of this new construction of childhood. Finally, we consider the possible messages conveyed by such presentations to perpetrators and victims of abuse.     

Linear scalar-on-surface random effects regression models

Many research fields increasingly involve analyzing data of a complex structure. Models investigating the dependence of a response on a predictor have moved beyond the ordinary scalar-on-vector regression. We propose a regression model for a scalar response and a surface (or a bivariate function) predictor. The predictor has a random component and the regression model falls in the framework of linear random effects models. We estimate the model parameters via maximizing the log-likelihood with the ECME (Expectation/Conditional Maximization Either) algorithm. We use the approach to analyze a data set where the response is the neuroticism score and the predictor is the resting-state brain function image. In the simulations we tried, the approach has better performance than two other approaches, a functional principal component regression approach and a smooth scalar-on-image regression approach.     

Communication in Statistics-Theory and methods improved GQL estimation method for the generalised BINMA(1) model

In a recent research, the quasi-likelihood estimation methodology was developed to estimate the regression effects in the Generalized BINMA(1) (GBINMA(1)) process. The method provides consistent parameter estimates but, in the intermediate computations, moment estimating equations were used to estimate the serial- and cross-correlation parameters. This procedure may not result optimal parameter estimates, in particular, for the regression effects. This paper provides an alternative simpler GBINMA(1) process based on multivariate thinning properties where the main effects are estimated via a robust generalized quasi-likelihood (GQL) estimation approach. The two techniques are compared through some simulation experiments. A real-life data application is studied.     

Bivariate,multivariate, and matrix variate normal characterizations: A brief survey II

The paper entitled “Bivariate and Multivariate Normal Characterizations: A Brief Survey,” by Hamedani, which was published in 1992, covered the published characterizations of bivariate and multivariate normal (MVN) distributions from 1941 to 1991. The present work is a follow-up to the 1991/1992 survey which includes not only characterizations of the bivariate and MVN distributions, but also characterizations of the matrix variate normal distribution, which have appeared from 1991/1992 to the present.     

Construction of bivariate and multivariate weighted distributions via conditioning

Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this article, we propose an alternative method to construct a new family of bivariate and multivariate weighted distributions. For illustrative purposes, some examples of the proposed method are presented. Several structural properties of the bivariate weighted distributions including marginal distributions together with distributions of the minimum and maximum, evaluation of the reliability parameter, and verification of total positivity of order two are also presented. In addition, we provide some multivariate extensions of the proposed models. A real-life data set is used to show the applicability of these bivariate weighted distributions.     

Bivariate extension of (dynamic) cumulative past entropy

Recently, the concept of cumulative residual entropy (CRE) has been studied by many researchers in higher dimensions. In this article, we extend the definition of (dynamic) cumulative past entropy (DCPE), a dual measure of (dynamic) CRE, to bivariate setup and obtain some of its properties including bounds. We also look into the problem of extending DCPE for conditionally specified models. Several properties, including monotonicity, and bounds of DCPE are obtained for conditional distributions. It is shown that the proposed measure uniquely determines the distribution function. Moreover, we also propose a stochastic order based on this measure.     

新中国十七年图像文化研究的学术史回顾

随着20世纪80年代西方的图像文化史作为新兴的研究方法进入中国,中国不同历史时期的图像文化生产与传播备受研究者的关注。同时,西方图像学研究为各类文学、美术、电影等作品的解读提供了较为充分的理论支持,研究者把图像学理论与文本分析有机结合,展开了艺术学与文化研究的批评实践。"十七年"时期的图像文化具有独特的历史与美学价值,目前已经成为学界研究的热点,有进行学术史回顾与反思的必要。通过对现有的"十七年"时期图像文化研究成果的整合分析,可以展现中国图像文化研究的最新进展以及西方图像学方法在中国的本土化实践。     

Modern likelihood inference for the maximum/minimum of a bivariate normal vector

ABSTRACT

We consider the use of modern likelihood asymptotics in the construction of confidence intervals for the parameter which determines the skewness of the distribution of the maximum/minimum of an exchangeable bivariate normal random vector. Simulation studies were conducted to investigate the accuracy of the proposed methods and to compare them to available alternatives. Accuracy is evaluated in terms of both coverage probability and expected length of the interval. We furthermore illustrate the suitability of our proposals by means of two data sets, consisting of, respectively, measurements taken on the brains of 10 mono-zygotic twins and measurements of mineral content of bones in the dominant and non-dominant arms for 25 elderly women.