Mentoring School-Age Children: A Classification of Programs

The number of mentoring programs providing adult support to youth has increased dramatically in recent years. This report presents information on the characteristics of programs serving school-aged youth (K-12). We found that rather than simply replicating the traditional Big Brothers Big Sisters model, newer programs are emphasizing somewhat more instrumental goals and activities, as well as experimenting with different types of relationships (group, school-based, etc.). Most programs seem to have sufficient infrastructure to screen, train, and supervise their mentors adequately, but many de-emphasize the importance of developing long-term relationships

PRESERVATION OR DEVELOPMENT: COMPETING USES OVER THE FUTURE OF FARMLAND IN URBANIZING AREAS

Land use, farmland preservation, competing risks models, multinomial logit models, Resource /Energy Economics and Policy,

Disposition toward privacy and information disclosure in the context of emerging health technologies.

ObjectiveWe sought to present a model of privacy disposition and its development based on qualitative research on privacy considerations in the context of emerging health technologies.Materials and methodsWe spoke to 108 participants across 44 interviews and 9 focus groups to understand the range of ways in which individuals value (or do not value) control over their health information. Transcripts of interviews and focus groups were systematically coded and analyzed in ATLAS.ti for privacy considerations expressed by respondents.ResultsThree key findings from the qualitative data suggest a model of privacy disposition. First, participants described privacy related behavior as both contextual and habitual. Second, there are motivations for and deterrents to sharing personal information that do not fit into the analytical categories of risks and benefits. Third, philosophies of privacy, often described as attitudes toward privacy, should be classified as a subtype of motivation or deterrent.DiscussionThis qualitative analysis suggests a simple but potentially powerful conceptual model of privacy disposition, or what makes a person more or less private. Components of privacy disposition are identifiable and measurable through self-report and therefore amenable to operationalization and further quantitative inquiry.ConclusionsWe propose this model as the basis for a psychometric instrument that can be used to identify types of privacy dispositions, with potential applications in research, clinical practice, system design, and policy

Resilience Capacity and Strategic Agility: Prerequisites for Thriving in a Dynamic Environment

organizational resilience, strategic agility, competitive dynamics

Margin-based Ranking and an Equivalence between AdaBoost and RankBoost

We study boosting algorithms for learning to rank. We give a general margin-based bound for ranking based on covering numbers for the hypothesis space. Our bound suggests that algorithms that maximize the ranking margin will generalize well. We then describe a new algorithm, smooth margin ranking, that precisely converges to a maximum ranking-margin solution. The algorithm is a modification of RankBoost, analogous to “approximate coordinate ascent boosting.” Finally, we prove that AdaBoost and RankBoost are equally good for the problems of bipartite ranking and classification in terms of their asymptotic behavior on the training set. Under natural conditions, AdaBoost achieves an area under the ROC curve that is equally as good as RankBoost’s; furthermore, RankBoost, when given a specific intercept, achieves a misclassification error that is as good as AdaBoost’s. This may help to explain the empirical observations made by Cortes andMohri, and Caruana and Niculescu-Mizil, about the excellent performance of AdaBoost as a bipartite ranking algorithm, as measured by the area under the ROC curve

Girls Count: A Global Investment & Action Agenda

Explains how girls' welfare affects overall economic and social outcomes. Outlines steps to disaggregate health, education, and other data by age and gender; invest strategically in girls' programs; and ensure equitable benefits for girls in all sectors