Anticipating Likely Consequences of Lottery‐Based Affirmative Action*

Objectives. To better understand the consequences of whole or partial reliance on test scores as a screening mechanism for college or university admissions or for job placement or promotion. Methods. We introduce a simple hurdles/threshold model to study one particular mechanism that has been recently proposed to generate a “compromise” between race‐normed or gender‐normed standards for acceptance, on the one hand, and the decision to select those with the highest score regardless of race or gender, on the other—a method we call lottery‐based rules with minimum thresholds of acceptance. Results. We show the factors that determine how close acceptance rates for the disadvantaged group under lottery‐based methods will be to the acceptance rates under either race‐normal or pretest‐score‐based mechanisms. Conclusions. We argue that the likely consequences of using this method are not nearly as attractive as they might first appear to reformers.     

Policy Learning for Flood Mitigation: A Longitudinal Assessment of the Community Rating System in Florida

Floods continue to inflict the most damage upon human communities among all natural hazards in the United States. Because localized flooding tends to be spatially repetitive over time, local decisionmakers often have an opportunity to learn from previous events and make proactive policy adjustments to reduce the adverse effects of a subsequent storm. Despite the importance of understanding the degree to which local jurisdictions learn from flood risks and under what circumstances, little if any empirical, longitudinal research has been conducted along these lines. This article addresses the research gap by examining the change in local flood mitigation policies in Florida from 1999 to 2005. We track 18 different mitigation activities organized into four series of activities under the Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) for every local jurisdiction in Florida participating in the FEMA program on a yearly time step. We then identify the major factors contributing to policy changes based on CRS scores over the seven-year study period. Using multivariate statistical models to analyze both natural and social science data, we isolate the effects of several variables categorized into the following groups: hydrologic conditions, flood disaster history, socioeconomic and human capital controls. Results indicate that local jurisdictions do in fact learn from histories of flood risk and this process is expedited under specific conditions.     

A Spatio‐Temporal Exposure‐Hazard Model for Assessing Biological Risk and Impact

We developed a simulation model for quantifying the spatio‐temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio‐temporal exposure‐hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (b iological risk a ssessment with R ) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.     

Retrospective accounts of first exposure to minoritized sexual and gender identities

Although there has been considerable research about attitudes towards LGBTQ+ people, there has been little research into how people first come to be aware of minoritized sexual and gender minority (SGM) identities. This study sought to address this gap. A sample of sexual minority (n = 150) and heterosexual (n = 802) young adults (N = 952; M_age = 18.88 years, SD = 1.75; 949 were cisgender, three were transgender), primarily recruited from a large southern university, were asked retrospectively to recount their first exposure to or awareness of SGM identities. Responses between SGM and heterosexual participants were compared through a variety of analytical approaches, including analyzing themes about the source from which participants first recalled encountering these identities, and whether understanding about these identities came through a personal connection to someone with these identities. SGM participants reported encountering minoritized sexual identities a year earlier than did heterosexual participants, with both groups encountering these concepts in middle childhood, on average. SGM participants were more likely than heterosexual participants to report learning about minoritized gender identities from someone with a minoritized gender identity, while heterosexual participants more often reported learning about these identities from media or celebrities. Heterosexual (vs. SGM) participants were also more likely to imply that minoritized gender identities were adopted to be popular, rather than being authentic identities in themselves. Framed by developmental intergroup theory (DIT), we discuss implications of these findings, especially potential interrelationships with the development of prejudiced attitudes about SGM identities.     

Nonparametric asymptotic confidence intervals for extreme quantiles

In this paper, we propose new asymptotic confidence intervals for extreme quantiles, that is, for quantiles located outside the range of the available data. We restrict ourselves to the situation where the underlying distribution is heavy-tailed. While asymptotic confidence intervals are mostly constructed around a pivotal quantity, we consider here an alternative approach based on the distribution of order statistics sampled from a uniform distribution. The convergence of the coverage probability to the nominal one is established under a classical second-order condition. The finite sample behavior is also examined and our methodology is applied to a real dataset.     

Personality predictors of career exploration: A meta-analysis

In this meta-analysis, correlations of personality traits and career decision-making self-efficacy with self and environmental career exploration were estimated across 71 samples and a pairwise sample of 19,846. Traits included the Big Five personality traits, shyness, locus of control, vocational decision styles, and stress. Many measures of career exploration were based on scores of self and environmental exploration on the Career Exploration Survey. Results varied by characteristics with the largest effects for locus of control, vocational decision style: thinking-feeling and self-efficacy. Environmental exploration and self-exploration were moderately correlated and demonstrated different relations with traits that were consistent with theory. Self-exploration was related to openness to experience and unrelated to extraversion, while environmental exploration was correlated with extraversion. Both were similarly correlated with conscientiousness such that conscientious individuals were more likely to engage in career exploration.     

Using social media-based drama therapy and family counselling to treat symptoms of postpartum depression among women

This study examines the impact of social media-based drama therapy and family counselling in reducing symptoms of postpartum depression (PPD) in women aged 18–34. The researchers used a quasi-experimental design and randomly assigned the participants (n = 303) to the control, drama therapy, and family counselling groups. The key findings of the study are as follows. First, at baseline, women not only showed more symptoms of PPD than their male counterparts, but men also reached the PPD threshold of 12/13. Second, the difference between women and men regarding their PPD scores achieved statistical significance (p = 0.004). However, during the post-intervention assessment, men who received drama therapy intervention reported a significant drop in their PPD below the threshold of 12/13. Only women whose spouses received family counselling on spousal support reported a significant drop in their PPD. However, those whose partners did not receive family counselling on spousal support still reported PPD scores within the threshold. In both instances, women in the control group still had high PPD scores. Finally, during the 6-month follow-up assessment, even men in the control group did not have significant symptoms of PPD as their scores dropped below the threshold. On the contrary, women in the control group still had high PPD, indicating that PPD lasted more in women than in men. Also, women whose husbands received family counselling on spousal support reported PPD scores below the threshold. However, women whose husbands did not receive spousal counselling still had PPD scores at the threshold, even though their scores marginally dropped.     

The Design of Feature‐Limited Demonstration Software: Choosing the Right Features to Include

Today, software supports many important tasks in a variety of industries. In the specialized nature of these environments, a common problem faced by software vendors is to correctly signal the true value of a software product to the end users. For example, telecommunications equipment manufacturers design complex software for important functions like provisioning new users in the network. These software products automate various functions that would otherwise need to be done manually. In order to enable potential customers—telecommunications providers—to evaluate and recognize the full value of the product, equipment vendors often provide a free, feature‐limited version of the product to the customer. As the specific features included in the feature‐limited version influence whether the full product is purchased or not, it is essential that the features included in the feature‐limited version be selected judiciously. While the importance of identifying the best set of features has been well recognized, there has been little research to date that systematically addresses this fundamental business decision. This study fills this gap in the literature by providing an objective approach to the design of demonstration software. We illustrate the benefits of our approach through a case study involving the design of a feature‐limited demo for a wireless telecommunications equipment manufacturer.