A SOCIOLOGY FOR OUR TIMES: Alvin Gouldner's Message

For the St. Louis meeting of the Midwest Sociological Society, the author organized a special session to reflect on the particular sociological tradition associated with Washington University, with a particular focus on Alvin Gouldner's work. From that session came this symposium, for which various papers presented were developed into articles. The session and these articles raise important issues for what they tell us both about Gouldner's work and about where sociology is as a discipline today. Among these issues are (1) the optimistic quest for objective value-free knowledge positivism entailed in the past versus a self-reflexive quest for knowledge that entails a tragic acceptance of its limits at present, (2) the effort to distinguish social theory from sociology, ideology, and politics, with all of whom it overlaps as they strive to be both social diagnosis and social therapy, (3) the production of knowledge as dependent both on the lived experiences that shape our biographies and on the intellectual influences available in the local settings where we work, (4) the effort to warn us against the various excesses to which our disciplinary and personal commitments give way, and (5) the role social theory can play as a search light that illuminates our way in the darkness of the empirical world in which we live, while it simultaneously casts a shadow.     

Age difference asymmetry and a two-sex perspective

The paper shows that (a) the age difference between spouses can be and has been different for men and women; (b) male and female age differences can exhibit different trends; (c) the discrepancy is due to remarriage; (d) the age difference fluctuates substantially through time; (e) trends in the age difference are not readily interpretable as reflecting change in the relative status of the sexes; and (f) that trends in the age difference may be linked to marriage market conditions. The paper argues that marriage and fertility data for both men and women are increasingly necessary because of rises in marital breakdown and the associated divergence of the experience of men and women.Cet article montre que (a) les différences d'âge entre époux peuvent être et ont été dissemblables pour les hommes et les femmes; (b) les différences d'âge masculines et féminines peuvent présenter des tendances différentes; (c) la divergence est due aux remariages; (d) les différences d'âge varient de façon importante au cours du temps; (e) les tendances dans les différences d'âge ne sont pas simplement interprétables en termes de changements dans le statut relatif des sexes; et (f) les tendances dans les différences d'âge peuvent être reliées aux conditions du marché matrimonial. L'article montre que les données sur le mariage et la fécondité à la fois des hommes et des femmes, sont de plus en plus nécessaires du fait de l'accroissement des ruptures d'unions et de la divergence des expériences masculines et féminines, qui lui est associée.

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An earlier version of this paper, His and her age gap: asymmetry in the age difference between partners, was a contributed paper to Session F27 of the General Conference of the International Union for the Scientific Study of Population, New Delhi, 20–27 September 1989. A longer version appeared as LS Working Paper 70, issued by City University Social Statistics Research Unit, September 1990.     

Women and Poverty in Spain (1981--1991)

Social Indicators Research -     

Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

Bayesian influence diagnostics in radiocarbon dating

Linear models constitute the primary statistical technique for any experimental science. A major topic in this area is the detection of influential subsets of data, that is, of observations that are influential in terms of their effect on the estimation of parameters in linear regression or of the total population parameters. Numerous studies exist on radiocarbon dating which propose a value consensus and remove possible outliers after the corresponding testing. An influence analysis for the value consensus from a Bayesian perspective is developed in this article.     

Lower posterior death probabilities from a quick medical response in road traffic accidents

Introduction: We use data from Spain on roads and motorways traffic accidents in May 2004 to quantify the statistical association between quick medical response time and mortality rate. Method: Probit and logit parameters are estimated by a Bayesian method in which samples from the posterior densities are obtained through an MCMC simulation scheme. We provide posterior credible intervals and posterior partial effects of a quick medical response at several time levels over which we express our prior beliefs. Results: A reduction of 5 min, from a 25-min response-time level, is associated with lower posterior probabilities of death in roads and motorways accidents of 24% and 30%, respectively.     

Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

A pivotal characteristic of credit defaults that is ignored by most credit scoring models is the rarity of the event. The most widely used model to estimate the probability of default is the logistic regression model. Since the dependent variable represents a rare event, the logistic regression model shows relevant drawbacks, for example, underestimation of the default probability, which could be very risky for banks. In order to overcome these drawbacks, we propose the generalized extreme value regression model. In particular, in a generalized linear model (GLM) with the binary-dependent variable we suggest the quantile function of the GEV distribution as link function, so our attention is focused on the tail of the response curve for values close to one. The estimation procedure used is the maximum-likelihood method. This model accommodates skewness and it presents a generalisation of GLMs with complementary log–log link function. We analyse its performance by simulation studies. Finally, we apply the proposed model to empirical data on Italian small and medium enterprises.