Initiating Sexual Experiences: How Do Young Adolescents Make Decisions Regarding Early Sexual Activity?

Understanding how young adolescents make decisions to engage in early sexual activities is vital for intervention efforts aimed at fostering positive youth development and reducing the negative outcomes of adolescent sexual behavior. In‐depth interviews with 42 suburban, mostly White, ninth‐grade adolescents (52% females, mean age=14.1, SD=.45) elicited accounts of their early sexual decisions. We adapted grounded theory methodology to build a model of sexual decision making from the adolescents' narratives. Six dominant categories emerged: contextual factors (relationship and personal characteristics), consideration of risks and benefits, boundary setting, boundary communication, the sexual experience, and evaluation. Our model of early sexual decision‐making processes, developed from the perspectives of young adolescents, highlights active consideration of health and social risks and benefits, as well as the generation of options regarding sexual activity. The model also shows that young adolescents set clear boundaries of sexual limits and evaluate sexual experiences, suggesting a dynamic process of decision making.     

The negative social network: when friends are foes

In this study, three factors appear to influence significantly whether a child in foster care would be returned to the parent. The factors proved to be the number of persons in the parent's home, the number of friends in the neighborhood, and the frequency with which the parent saw those friends.     

Measuring the quality of economic forecasts

Most evaluations of forecasts have hitherto been primarily based on measure of statistical accuracy. Attention is drawn to the need for concentrating instead on the forecast components bearing on managerial decisions and on the economic effects of such decisions. The method suggested highlights the changing locus of the most influential errors over various time horizons. It also takes account of the economic consequences of under-estimates and over-estimates in forecasting, as well as of the penalties of belated correcting actions. Finally, some broader implications of this approach are discussed.     

Lot Splitting in Stochastic Flow Shop and Job Shop Environments*

In recent years many firms have been implementing small lot size production. Lot splitting breaks large orders into smaller transfer lots and offers the ability to move parts more quickly through the production process. This paper extends the deterministic studies by investigating various lot splitting policies in both stochastic job shop and stochastic flow shop settings using performance measures of mean flow time and the standard deviation of flow time. Using a computer simulation experiment, we found that in stochastic dynamic job shops, the number of lot splits is more important than the exact form of splitting. However, when optimal job sizes are determined for each scenario, we found a few circumstances where the implementation of a small initial split, called a “flag,” can provide measurable improvement in flow time performance. Interestingly, the vast majority of previous research indicates that methods other than equal lot splitting typically improves makespan performance. The earlier research, however, has been set in the static, deterministic flow shop environment. Thus, our results are of practical interest since they show that the specific method of lot splitting is important in only a small set of realistic environments while the choice of an appropriate number of splits is typically more important.     

USE OF OPTIMIZATION AND SIMULATION MODELS TO ANALYZE OUTPATIENT HEALTH CARE SETTINGS*

An important problem facing the manager of an outpatient health care clinic involves determining the best combination of services, facilities, and personnel to maximize profits and simultaneously achieve acceptable measures of the clinic's daily performance. This problem is often attacked using either linear programming or computer simulation. This paper uses a recursive optimization-simulation approach which takes advantage of the best features of both optimization and simulation while minimizing the disadvantages of each method used alone. Results from a hypothetical setting using data from several actual settings demonstrate the value of the recursive method.     

Correction to: Between Collaboration and Subordination: State and Non-state Actors in Russian Anti-drug Policy

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper was intended for the present special section Civil Society in Authoritarian and Hybrid Regimes, but published...     

On a Class of Random Probability Measures with General Predictive Structure

Abstract. In this study, we investigate a recently introduced class of non‐parametric priors, termed generalized Dirichlet process priors. Such priors induce (exchangeable random) partitions that are characterized by a more elaborate clustering structure than those arising from other widely used priors. A natural area of application of these random probability measures is represented by species sampling problems and, in particular, prediction problems in genomics. To this end, we study both the distribution of the number of distinct species present in a sample and the distribution of the number of new species conditionally on an observed sample. We also provide the Bayesian Non‐parametric estimator for the number of new species in an additional sample of given size and for the discovery probability as function of the size of the additional sample. Finally, the study of its conditional structure is completed by the determination of the posterior distribution.     

Between Collaboration and Subordination: State and Non-state Actors in Russian Anti-drug Policy

Due to weak state and administrative capacity, the Russian government has involved resource-rich non-state actors into policy-making since about 2005 and established numerous institutionalized platforms, networks, and forums. These networks mainly emerge on regional and local levels and are designed to generate policy advice, implement decisions, and contribute to output legitimacy. A crucial question is how the authorities govern and regulate these bodies under the terms of a hybrid regime. The paper sheds light on why and how state authorities interact with non-state actors and unravels functions and flavors of governance networks in Russia. Drawing on the empirical results of case studies on anti-drug policy conducted in the regions Samara and St Petersburg, the paper reveals that state dominance within networks is a significant characteristic, although authorities rarely apply explicit ‘hard’ tools of government onto collaborations with non-state actors. The paper also allows for theorizing on the role of governance networks in a hybrid regime.

     

THE EFFECTIVENESS OF EXTENDING THE HORIZON IN ROLLING PRODUCTION SCHEDULING

In recent work, Baker [1] has investigated the use of rolling schedules for multiperiod production scheduling problems. One of his results is that the longest possible forecast horizon is not necessarily the best. He also found that the rolling schedules' effectiveness fluctuates widely depending upon the length of the forecast horizon. To smooth these fluctuations we have investigated use of forecasting to extend the problem horizon. Some of our results confirm the previous conclusions, but other results support the position that “the more information the better.”