Gender, home and family in cultural capital theory

The paper argues that Bourdieu's stress on early familiarization for the highest value of cultural capital is closely linked to his idea, strongly emphasized in Distinction, about the role of family and domestic life for individual development and social positions. The role of women, as mothers and homemakers, is crucial in this process. Yet, Bourdieu defines social origin as deriving from the father. The centrality to Bourdieu's thinking of a resilient traditional pattern of masculine domination and feminine submission constitutive of the Western gender habitus explains both his stress on ‘normalcy’ for the production of legitimate dispositions, and his resistance to incorporating into his thinking the implications of recent transformations in home family living, which have destabilized the gender order. It is thus important to consider contemporary feminist analyses of the family and home life and their significance for a renewed theory of cultural capital. The paper considers two sets of literature. Firstly, it addresses the manners in which home and family are conceptualized in Bourdieu's key texts where these issues were prominent in the development of his thinking on cultural capital. The second set of literature includes texts by feminist academics in the fields of family, gender and the body, which analyse the destabilizing of the gender order and everyday family living in contemporary society. Two questions are addressed on the basis of these reflections: (1) Is cultural capital an individual or a household resource? (2) How does cultural capital relate to personal interdependencies at the level of family and households?     

A Note on Influence Assessment in Score Tests

Recently, [1] Ebrahimi, N. 1996. How to measure uncertainty about residual life time. Sankhya Ser. A, 58: 48–57.  [Google Scholar] proposed a dynamic measure based on differential entropy applied to the residual lifetime. This measure has been used for the classification and ordering of survival functions. More recently, [2] Ebrahimi, N. 1997. Testing whether lifetime distribution is decreasing uncertainty. Journal of Statistical Planning and Inference, 64: 9–19. [Crossref], [Web of Science ®] , [Google Scholar] has considered the problem of testing the monotonicity of this measure. We propose and study several kernel type estimators of the entropy of residual life through the estimation of f(x) log f(x). These estimators can be applied to the classification and comparison of lifetime distribution.     

Nenparametric Two-Group Classification: Concepts and a SAS-Based Software Package

This article introduces BestClass, a set of SAS macros, available in the mainframe and workstation environment, designed for solving two-group classification problems using a class of recently developed nonparametric classification methods. The criteria used to estimate the classification function are based on either minimizing a function of the absolute deviations from the surface which separates the groups, or directly minimizing a function of the number of misclassified entities in the training sample. The solution techniques used by BestClass to estimate the classification rule use the mathematical programming routines of the SAS/OR software. Recently, a number of research studies have reported that under certain data conditions this class of classification methods can provide more accurate classification results than existing methods, such as Fisher's linear discriminant function and logistic regression. However, these robust classification methods have not yet been implemented in the major statistical packages, and hence are beyond the reach of those statistical analysts who are unfamiliar with mathematical programming techniques. We use a limited simulation experiment and an example to compare and contrast properties of the methods included in Best-Class with existing parametric and nonparametric methods. We believe that BestClass contributes significantly to the field of nonparametric classification analysis, in that it provides the statistical community with convenient access to this recently developed class of methods. BestClass is available from the authors.     

On sufficient conditions for the strong consistency of least-squares estimates

The strong consistency of the least-squares estimates in regression models is obtained when the errors are i.i.d. with absolute moment of order r, 0<r? 2. The assumptions presented for the random error sequence will permit us to obtain improvements of the conditions on the regressors in order to obtain the strong consistency of the least-squares estimates in linear and nonlinear regression models.     

Strong consistency of least squares estimates with i.i.d. errors with mean values not necessarily defined

We establish strong consistency of the least squares estimates in multiple regression models discarding the usual assumption of the errors having null mean value. Thus, we required them to be i.i.d. with absolute moment of order r, 0<r<2, and null mean value when r>1. Only moderately restrictive conditions are imposed on the model matrix. In our treatment, we use an extension of the Marcinkiewicz–Zygmund strong law to overcome the errors mean value not being defined. In this way, we get a unified treatment for the case of i.i.d. errors extending the results of some previous papers.     

Geographically Weighted Negative Binomial Regression—incorporating overdispersion

Global regression assumes that a single model adequately describes all parts of a study region. However, the heterogeneity in the data may be sufficiently strong that relationships between variables can not be spatially constant. In addition, the factors involved are often sufficiently complex that it is difficult to identify them in the form of explanatory variables. As a result Geographically Weighted Regression (GWR) was introduced as a tool for the modeling of non-stationary spatial data. Using kernel functions, the GWR methodology allows the model parameters to vary spatially and produces non-parametric surfaces of their estimates. To model count data with overdispersion, it is more appropriate to use a negative binomial distribution instead of a Poisson distribution. Therefore, we propose the Geographically Weighted Negative Binomial Regression (GWNBR) method for the modeling of data with overdispersion. The results obtained using simulated and real data show the superiority of this method for the modeling of non-stationary count data with overdispersion compared with competing models, such as global regressions, e.g., Poisson and negative binomial and Geographically Weighted Poisson Regression (GWPR). Moreover, we illustrate that these competing models are special cases of the more robust model GWNBR.     

Validation of the Flourishing Scale and Scale of Positive and Negative Experience in Portugal

The Flourishing Scale (FS) and the Scale of Positive and Negative Experience (SPANE) created by Diener et al. (Soc Indic Res 97:143–156, 2010) are instruments that assess psychological flourishing and feelings (positive and negative, and the difference between the two). In this study, the psychometric properties of both scales were explored by using two Portuguese samples (I: n = 734; II: n = 194). Reliability analysis and a multi-group confirmatory factorial analysis (MCFA) of both scales were performed. To examine the validity of FS and SPANE we analyzed their correlations with other well-being and happiness measures. Results showed that the Portuguese versions of both scales have good psychometric properties, and they also showed convergent validity. Results also demonstrated the unidimensional structure of the FS and a two-factor solution for the SPANE. The multi-group CFA of both scales evidenced an invariant structure. Both Portuguese versions of the scales behave consistently with the original and may be used in future studies of well-being.     

Problems with Traditional Science Publishing and Finding a Wider Niche for Post-Publication Peer Review

Science affects multiple basic sectors of society. Therefore, the findings made in science impact what takes place at a commercial level. More specifically, errors in the literature, incorrect findings, fraudulent data, poorly written scientific reports, or studies that cannot be reproduced not only serve as a burden on tax-payers’ money, but they also serve to diminish public trust in science and its findings. Therefore, there is every need to fortify the validity of data that exists in the science literature, not only to build trust among peers, and to sustain that trust, but to reestablish trust in the public and private academic sectors that are witnessing a veritable battle-ground in the world of science publishing, in some ways spurred by the rapid evolution of the open access (OA) movement. Even though many science journals, traditional and OA, claim to be peer reviewed, the truth is that different levels of peer review occur, and in some cases no, insufficient, or pseudo-peer review takes place. This ultimately leads to the erosion of quality and importance of science, allowing essentially anything to become published, provided that an outlet can be found. In some cases, predatory OA journals serve this purpose, allowing papers to be published, often without any peer review or quality control. In the light of an explosion of such cases in predatory OA publishing, and in severe inefficiencies and possible bias in the peer review of even respectable science journals, as evidenced by the increasing attention given to retractions, there is an urgent need to reform the way in which authors, editors, and publishers conduct the first line of quality control, the peer review. One way to address the problem is through post-publication peer review (PPPR), an efficient complement to traditional peer-review that allows for the continuous improvement and strengthening of the quality of science publishing. PPPR may also serve as a way to renew trust in scientific findings by correcting the literature. This article explores what is broadly being said about PPPR in the literature, so as to establish awareness and a possible first-tier prototype for the sciences for which such a system is undeveloped or weak.     

Reviews

Book reviewed in this article: Bidge's Mob: Written and illustrated by Gaye Dell Creative Family Therapy Techniques: Play, Art, and Expressive Activities to Engage Children in Family Sessions: Editor: Liana Lowenstein Essential Skills in Family Therapy, from the first interview to termination: JoEllen Patterson, Lee Williams, Todd M. Edwards, Larry Chamow, Claudia Grauf‐Grounds Multi‐Family Therapy: Concepts and Techniques: Eia Asen, Michael Scholz