The relationship between education, experience, and police performance

This study used data from 299 police officers from 12 municipal police departments across the state of Virginia to determine the relationship between education and police performance. Performance was measured by supervisor evaluations of each officer's overall performance, communication skills, public relations skills, report writing skills, response to new training, decision making ability, and commitment to the police department. Significant correlations were found between education and most measures of performance. Most importantly, the results show a significant correlation between overall performance and education (r=24, p.<001). The only variables not proving to be significantly related to education were objective measures of the volume of arrests, number of times the officer required discipline, and number of accidents. Interestingly, the benefits of a college education do not become apparent until police officers gain experience. In addition, police, officers with only a high school diploma decreased in overall performance after five years of experience.     

India's “Grand Strategy” for the Indian Ocean: Mahanian Visions

This article considers how India sees the Indian Ocean, and in particular its drive to make the Indian Ocean, “India's Ocean.” Various comparisons and links are made. Firstly there is the role and application of Mahanian tenets of “sea-power,” in particular naval projection, control of sea-routes and access to bases. Second is the contrast between the earlier maritime visions of Kavalam Panikkar (1945) and Keshav Vaidya (1949) and the continental mindset evident under Nehru and his successors which saw neglect of India's maritime power. Third is the strategic vision evident since 1998 with the BJP government and maintained by the Congress administration since 2004. This has underpinned India's Naval Chief of Staff Arun Prakash's current eloquence on the possibilities opening up for India in and around the Indian Ocean. Questions of intent (strategic doctrine) and the application of “state power” (spending, bases, ships and equipment, geographical reach) are woven together.     

Fertility,development, and family planning, 1970–1980: An analysis of cases weighted by population

A series of related studies (Freedman and Berelson, 1976; Mauldin and Berelson, 1978; and Tsui and Bogue, 1978) have presented empirical findings based on multiple regression analysis which indicated that family planning program effort (FP), as measured by an index developed by Lapham and Mauldin (1972), was the single most important predictor of (or influence on) fertility reduction in less-developed countries (LDCs). The basic results have been confirmed repeatedly. A more extensive data set was used to extend the analysis to a comparison of results of corss-sectional models circa 1970 and 1980. The study builds upon the results of past studies yet differs from them in several ways. All the variables in the present study were measured at 2 points in time: circa 1970 and circa 1980, allowing a comparison between cross-sectional models for 1970 and 1980. Among the cases included in this multivariate analysis was China, a country usually excluded for lack of data. The analysis was extend to 85 countries. Cases were weighted by population, having the effect of increasing the impact of larger countries such as India and China on the outcome of the analysis. Total fertility rate (TFR) was used as an indicator of fertility. For 1970, family planning program effort had the strongest direct influence on fertility (a result consistent with previous studies). Life expectancy at birth was the other direct influence. The direct influence of life expectancy at birth was less than that of family planning, but the total influence was greater. After life expectancy and family planning, school enrollment and relative educational status of women had the strongest indirect and total influences. The other variables all had a positive influence on fertility. When the total variance attributable was considered, directly and indirectly to each of the independent variables, urbanization, carlorie supply, and per capita gross national product all accounted for less than 5% of the variance in fertility, all of it indirect. Life expectancy, family planning, and school enrollment each explained (directly plus indirectly) more than 10% of the variance in fertility. The pattern differed somewhat for 1980. Calorie supply, per capita gross national product, and relative educational status of women had no influence, direct or indirect on fertility. Also for 1980, life expectancy had a stronger direct influence on fertility than family planning. Overall, life expectancy at birth, family planning program effort, and total school enrollment emerged as the principal influences on fertility.     

Evaluating adolescent decision making in legal contexts

Challenges the use by policy researchers of a model for comparing adolescent and adult decision making that is based on informed consent standards. An expanded decision-making framework designed to evaluate judgment in adults and adolescents can better test the empirical basis of paternalistic legal policies. The theoretical and empirical literature on the informed consent framework is critiqued and an alternative framework incorporating judgment factors is proposed. Three judgment factors—temporal perspective, attitude toward risk, and peer and parental influence—and their effects on decision making are explored. Finally, implications for future research are analyzed in several decision-making contexts.Several of the ideas in this article were originally presented by the first author and were published as part of a symposium on competence (see Scott, 1992). The current article expands and refines these ideas, provides a more substantial research base, and suggests several future research directions. We thank Joseph Allen, Richard Bonnie, Baruch Fischhoff, William Gardner, John Monahan, Edward Mulvey, Richard Redding, Paul Slovic, and three anonymous reviewers for their helpful comments. Special thanks to Thomas Grisso for providing much constructive criticism and to Wendy Shang for outstanding research assistance. Finally, we would like to acknowledge the MacArthur Foundation, which supported this work in its early stages.     

Inequality and fertility

This article focuses on the relationship between inequality and fertility, with empirical analysis only of direct influences. Whereas much of the literature seems to be based on 0-order correlations, the present study uses multiple regression analysis to test the strength of the evidence for a relationship between inequality and fertility when competing hypotheses are also considered. In addition, this study attempts to clarify some of the issues surrounding the measurement of inequality and to show how these may affect empirical results. It appears from the results presented here that research into the relative status of women as an influence on fertility holds considerable promise. In particular, it is interesting that a measure of the relative status of women (ratio of female school enrollment to male school enrollment) that is highly correlated with absolute educational status of people in the nation in general, and even more highly correlated with absolute educational status of women, emerges as one of 3 important predictors of fertility. The other measure of the relative educational status of women (female school enrollment ratio minus male school enrollment ratio), which has lower correlations with absolute educational status both of women and people in general, does not appear important, although it should be an equally valid indicator of women's status. It also has lower correlations with total fertility rates. 1 focus of further research should be an attempt to disentangle the effects of the relative status of women from absolute status of women and absolute status of people in the nation as a whole. Less promising is the prospect of future work on the relationship between income inequaltiy and fertility. The results are unencouraging with respect to both sampling problems and the actual magnitude of the effect of inequality on fertility. Overall, it appears that the importance of income inequality as an influence on fertility may have been overstated in the past.