Feminist and empowerment theory and social work practice

Feminist and empowerment theories are especially important to the understanding of individual and sociopolitical levels of social work assessment and intervention. Incorporating feminist and empowerment approaches in practice will provide social workers with the knowledge, values and skills most likely to promote human rights and social justice. In this paper, we present an overview of both theories and illustrate them with a case example.     

Suicide Attempts by Adolescent Latinas: An Exploratory Study of Individual and Family Correlates

Epidemiological data show high rates of suicide attempts among adolescent Latinas. Few studies have addressed the psychosocial, cultural and family correlates of suicide attempts among this age group of a rapidly growing population. The authors studied 31 adolescent Hispanic females who were receiving mental health services; 14 girls had attempted suicide in the previous five years and 17 had never attempted suicide. The two groups of girls did not differ significantly with respect to demographic profiles, levels of depression, family type, acculturation, or self-esteem. However, as hypothesized, the mutuality between girls and their mothers was lower among suicide attempters. Maladaptive coping skills of withdrawal and wishful thinking were more commonly used by attempters, and non-attempters used emotional regulation and problem-solving more frequently. Findings are discussed within the context of the empirical and theoretical literature and implications for practice are considered.     

Career Self‐Efficacy and Perceptions of Parent Support in Adolescent Career Development

The authors examined the relative contributions of both proximal and distal supports to the career interests and vocational self‐efficacy in a multiethnic sample (N = 139) of middle school adolescents. Consistent with Social Cognitive Career Theory, it was found that (a) vocational self‐efficacy and career planning/exploration efficacy consistently predicted young adolescents' career interests across Holland (J. L. Holland, D. R. Whitney, N. S. Cole, & J. M. Richards, 1969) themes; (b) gender and career gender‐typing predicted interests in Realistic, Investigative, and Social careers; and (c) perceived parent support accounted for 29% to 43% of the total unique variance in vocational self‐efficacy for all Holland theme careers.     

Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

The NTEE classification system: tests of reliability/validity in the field of higher education

An analysis of the field of higher education reveals a surprisingly large number of classification errors within the (US) National Taxonomy of Exempt Entities database. Of the nearly 4,000 non-profit entities coded within the universe of institutions of higher education, we estimate that approximately 60 per cent were incorrectly included (Type II errors). Institutions incorrectly excluded from the higher education universe (Type I errors) represent roughly 10 per cent of the institutions coded correctly. These errors result primarily from assigning codes on the basis of the names of organisations (for example, College Park Towers is classified as a college, when it is in fact a housing complex for senior citizens) and from trying too hard to assign codes in ambiguous situations. The consequences can be significant for the users of these data, and we recommend raising bright warning flags while simultaneously enlisting the help of the entire non-profit sector in improving the classification coding process.The authors are with The Andrew W. Mellon Foundation. In addition to our colleagues on the staff of the Foundation, we wish to thank Helmut Anheier, Ted Bozovich, Harvey Dale, Virginia Hodgkinson, Stephen Noga and Christopher Toppe for helpful suggestions.