Pilot Study of Psychopathology Among Roman Catholic Secular Clergy

This pilot study gathered information regarding overall levels of psychopathology in a nationally selected, random sample of U.S. Roman Catholic secular (i.e., diocesan) priests using the Symptom Checklist-90-Revised (SCL-90-R; Derogatis, 2004). The study yielded a response rate of 45%. One-half of the participants reported marked psychological problems, with interpersonal sensitivity, anxiety, and depression most strongly correlated with the instrument’s overall index of psychopathology. Four dimensional scales were elevated (i.e., obsessive-compulsive, interpersonal sensitivity, depression, psychoticism), as were two indices (i.e., GSI, PST). Implications and directions for future research are discussed

L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework

Despite the importance of sparsity in many large-scale applications, there are few methods for distributed optimization of sparsity-inducing objectives. In this paper, we present a communication-efficient framework for L1-regularized optimization in the distributed environment. By viewing classical objectives in a more general primal-dual setting, we develop a new class of methods that can be efficiently distributed and applied to common sparsity-inducing models, such as Lasso, sparse logistic regression, and elastic net-regularized problems. We provide theoretical convergence guarantees for our framework, and demonstrate its efficiency and flexibility with a thorough experimental comparison on Amazon EC2. Our proposed framework yields speedups of up to 50x as compared to current state-of-the-art methods for distributed L1-regularized optimization

Assessing the Frontiers of Ultra-Poverty Reduction: Evidence from CFPR/TUP, an Innovative Program in Bangladesh

This paper uses household panel data to provide robust evidence on the effects of BRAC’s Targeting the Ultra-poor Program in Bangladesh. Our identification strategy exploits type-1 errors in assignment, comparing households correctly included with those incorrectly excluded, according to program criteria. Evidence from difference-in-difference matching and sensitivity analysis shows that participation had significant positive effects on income, food consumption and security, household durables, and livestock, but no robust impact on health, ownership of homestead land, housing quality and other productive assets. Using quantile difference-in-difference, we find that the income gains from program participation is smaller for the lowest two deciles.Ultra-poor, CFPR/TUP, BRAC, Bangladesh, Microfinance, Bangladesh, Assignment Error, Difference-in-Difference, Matching, Heteroskedasticity-Based Identification