A Comparative Evaluation of Police Suicide Rate Validity

The authors assessed sensitivity, specificity, and predictive value of official police suicide rates and compared them to municipal workers. Deaths officially classified as suicide, accidental, and undetermined were submitted to a panel of medical examiners for validation. Six cases originally in the accident and undetermined rubric were reclassified as suicide. Official police suicide rates had less sensitivity (83.3% compared to 92.3%) of actual suicides than municipal worker rates. Police suicide rates also showed a lower negative proportion than municipal worker rates (86.2% compared to 98.7%). A generalizable sensitivity proportion equation for assessing suicide rates in other police groups is presented.     

J scale models for preference behavior

Three models for preference behavior are developed within the framework of Coombs' theory of data, an absolute difference model, a ratio model, and a two-stage model. Each of these models describes a mechanism by which unilateral preferences may be determined on a unidimensionalJ scale. Differential implications of the models for response latencies are derived, and some early data employing an application of the unfolding technique are presented in support of the two-stage model.Based upon portions of the author's doctoral dissertation, University of Michigan, 1962. This research was supported in part by NSF Grant No. G5820 to Professor C. H. Coombs. The writer also wishes to thank Professor William Hays, who served as committee chairman and offered considerable support and assistance.     

Reference group data for the Reitan-Indiana Neuropsychological Test Battery for Young Children

This study presents a data set for a reference group on the Reitan-Indiana Neuropsychological Test Battery for Young Children. The data set is based on a sample of 224 children, ages 5 to 8 years, referred to a special services cooperative for academic or behavioral concerns during the years 1980 through 1993. Data are presented in terms of sample size, means, standard deviations, diagnostic classifications, and population characteristics. Previously published data sets are reviewed in comparison to this newly acquired data set. Potential advantages of this data set include the larger sample, contemporary data collection, and a sample drawn from a United States school-referred population.     

Kicking over the traces: A note in response to Zurif and Piñango (1999)

Zurif and Pi?ango (1999) claimed that they excluded the four agrammatic patients reported by Druks and Marshall (1991) from their review article because two of the patients were nonnative speakers of Hebrew and because the Hebrew sentences we used in our investigations were ungrammatical. In Druks and Marshall (1991) we have shown that the presence or the absence of a trace in two types of Hebrew passives had no effect on the patients' performance. Two patients, without comprehension deficits, performed equally well on both types of passives and two patients, with comprehension deficits, were equally impaired on both types. We remind Zurif and Pi?ango of our previous response to the claims of ungrammaticality of our materials (Druks & Marshall, 1992) and argue that there were no justifiable reasons for excluding these cases from the review. We also comment on Zurif and Pi?ango's (1999) and Grodzinsky's (2000) new proposal that the association of agrammatic comprehension should be with Broca's aphasia and not with agrammatism.     

Neural network modeling of risk assessment in child protective services

The advantages of using neural network methodology for the modeling of complex social science data are demonstrated, and neural network analysis is applied to Washington State Child Protective Services risk assessment data. Neural network modeling of the association between social worker overall assessment of risk and the 37 separate risk factors from the State of Washington Risk Assessment Matrix is shown to provide case classification results superior to linear or logistic multiple regression. The improvement in case prediction and classification accuracy is attributed to the superiority of neural networks for modeling nonlinear relationships between interacting variables; in this respect the mathematical framework of neural networks is a better approximation to the actual process of human decision making than linear, main effects regression. The implications of this modeling advantage for evaluating social science data within the framework of ecological theories are discussed.     

The power of the Brown v. Board of Education decision: theorizing threats to sustainability

Interviews with African American and White American elders capture the immediate power of the Brown v. Board of Education (1954) decision and the biography of its impact over time. This article reviews the lived experience of the decision and theorizes 3 threats to sustainability that ruthlessly undermined the decision over time: (a) the unacknowledged and enormous sacrifice endured by the African American community in the name of desegregation; b) the violent and relentless resistance to the decision by government officials, educators, and many White community members; and (c) the dramatic shrinkage of the vision of Brown from the dismantling of White supremacy to a technical matter of busing. Implications are drawn for the study of desegregation and for the study of sustainability of social justice more broadly.