Toward a formal theory of interactive resocialization: The case of adoptive parenthood

Resocialization is pulled out of its structuralist roots and recast into an interactionist framework. Building on a substantive theory of the resocialization experience of becoming an adoptive parent, three theoretical properties of interactionist resocialization are presented. These can be summarized as involving unlearning and relearning some aspects of a core identity; the interpretation and active reconstruction of that identity which has reciprocal effects on all actors involved; and finally, the effects of both situational and trans-situational norms that give shape to the resocialization experience. Suggestions are made for other substantive areas of research that could be used for comparative analysis in order to further refine a formal theory of interactionist resocialization.     

The Approved Social Worker -- Reflections on Origins

Correspondence to Pauline M. Prior, Department of Social Policy and Social Work, University of York, Heslington, York YO1 5DD. Summary The aim of this paper is to examine the role of social workersunder current mental health law, in order to see if the adventof the Approved Social Worker (ASW) represents any more thanthe re-appearance of old concepts in a new guise. It is arguedthat it is impossible for the ASW to be anything more than anupdated version of the Relieving Officer of the last century,in view of the fact that the Mental Health Act 1983 does notprovide a clear mandate for an effective professional advocateon behalf of mentally ill people.     

Integrating Career and Personal Counseling

Career and personal counseling are inextricably intertwined. Career problems have a strong emotional component. Career indecision and procrastination may be better interpreted as zeteophobia, the fear of career exploration. Trait and factor theory pictures career counseling as unrealistically simplistic and leads neophytes to view it as boring. Training all counselors to integrate career and personal counseling would lead to better service for clients.     

The analysis of incomplete data using stochastic covariates

In the development of many diseases there are often associated random variables which continuously reflect the progress of a subject towards the final expression of the disease (failure). At any given time these processes, which we call stochastic covariates, may provide information about the current hazard and the remaining time to failure. Likewise, in situations when the specific times of key prior events are not known, such as the time of onset of an occult tumour or the time of infection with HIV-1, it may be possible to identify a stochastic covariate which reveals, indirectly, when the event of interest occurred. The analysis of carcinogenicity trials which involve occult tumours is usually based on the time of death or sacrifice and an indicator of tumour presence for each animal in the experiment. However, the size of an occult tumour observed at the endpoint represents data concerning tumour development which may convey additional information concerning both the tumour incidence rate and the rate of death to which tumour-bearing animals are subject. We develop a stochastic model for tumour growth and suggest different ways in which the effect of this growth on the hazard of failure might be modelled. Using a combined model for tumour growth and additive competing risks of death, we show that if this tumour size information is used, assumptions concerning tumour lethality, the context of observation or multiple sacrifice times are no longer necessary in order to estimate the tumour incidence rate. Parametric estimation based on the method of maximum likelihood is outlined and is applied to simulated data from the combined model. The results of this limited study confirm that use of the stochastic covariate tumour size results in more precise estimation of the incidence rate for occult tumours.     

Robustness of testing the equality of two slopes in simple linear structural relationships

The usual test of the equality of two slopes in a simple structural relation-ship is the test formed from the normal approximation using the Fisher information matrix, assuming two explanatory variables are independent. This paper examines the robustness if the explanatory variables are, in fact, dependent. A more efficient estimator is derived for a matched pair situation.     

Comparison of three estimators of the number of species

We consider estimation of the number of cells in a multinomial distribution. This is one version of the species problem: there are many applications, such as the estimation of the number of unobserved species of animals; estimation of vocabulary size, etc. We describe the results of a simulation comparison of three principal frequent-ist' procedures for estimating the number of cells (or species). The first procedure postulates a functional form for the cell probabilities; the second procedure approxi mates the distribution of the probabilities by a parametric probability density function; and the third procedure is based on an estimate of the sample coverage, i.e. the sum of the probabilities of the observed cells. Among the procedures studied, we find that the third (non-parametric) method is globally preferable; the second (functional parametric) method cannot be recommended; and that, when based on the inverse Gaussian density, the first method is competitive in some cases with the third method. We also discuss Sichel's recent generalized inverse Gaussian-based procedure which, with some refine ment, promises to perform at least as well as the non-parametric method in all cases.     

Inequalities for variances of some functions of random variables

In this note we prove some inequalities for variances and other measures of deviation of functions of random variables. Based on these inequalities we find some corollaries concerning the variances of fractional powers of random variables and of sums of independent random variables.     

Estimating the Rayleigh distribution scale parameter from doubly censored samples—Some comments

In a recent paper in this journal, Lee, Kapadia and Brock (1980) developed maximum likelihood (ML) methods for estimating the scale parameter of the Rayleigh distribution from doubly censored samples. They reported convergence difficulties in attempting to solve numerically the nonlinear likelihood equation (LE). To mitigate these difficulties, they employed approximations to simplify the LE, but found that the solution of the resulting simplified equation can give rise to parameter estimates of erratic accuracy. We show that the use of approximations to simplify the LE is unnecessary. In fact, under suitable parametric transformation, the log-likelihood function is strictly concave, the ML estimate always exists, is unique and finite. Furthermore, the LE is easy to solve numerically. A numerical example is given to illustrate the computations involved.