The nonprofit leadership deficit: A case for more optimism

Recent headlines claim that a looming nonprofit leadership crisis will soon be precipitated by retiring baby boomers. Analysis of baby boom demographics, using national census data on the age distribution and other demographic characteristics of top leaders by sector, confirms the aging nonprofit workforce. However, the issue of whether the aging workforce portends a nonprofit leadership crisis, when analyzed within a theoretical framework of supply and demand in the market for nonprofit executives, reveals flaws in most commentaries about the leadership crisis. Workings of the labor market and nonprofit organizations themselves suggest trends that could be expected to affect labor supply and demand and mitigate a leadership deficit. Reasonable—and likely—market and organizational adjustments, including higher executive pay, increased labor force participation of older workers, skill acquisition of younger workers, possible consolidation of nonprofit organizations, board and volunteer skill sharing, and even venture philanthropy, can be expected to moderate the shock of baby boom retirements, much in the way that schools, job markets, and housing markets have accommodated the movement of this “bulging” generation through earlier decades of their lives.     

Testosterone and men's depression: the role of social behavior.

Medical research suggests that testosterone has positive effects on mood (thereby reducing the chances of depression), and social science research finds testosterone to be related to antisocial behavior, risk behavior, unemployment and low paying jobs, and being unmarried--factors known to be positively related to depression. Analysis of a sample of 4,393 men finds a parabolic model best fits the data. The relationship between testosterone and depression is inverse for men with below average testosterone and direct for those with above average testosterone. The relationship disappears for those with above average testosterone when controls for antisocial and risk behaviors and the absence of protective factors such as marriage and steady employment are in the equation. The relationship is unchanged for those with below average testosterone. The results help explain the difference between medical and social research findings. Mechanisms accounting for the findings are explored.     

Ethical Issues in Risk Communication: Continuing the Discussion

Proposed in this article is one possible framework for classifying multiple types of ethical issues in risk communication research and practice to help continue a discussion initiated in 1990 by Morgan and Lave. Some of the questions that each stage of the process for planning risk communication strategies appears to pose for ethics are discussed (e.g., selecting issues to be communicated, knowing the issue, dealing with constraints). Also discussed briefly are some issues raised by the possibility that risk communicators aspire to the status of a profession. The purpose is to foster discussion rather than issue a conclusive statement on the topic, because its very nature makes a definitive pronouncement indefensible.     

Emotional Reactivity and Emotional Regulation Strategies as Predictors of Social Behavior with Peers During Toddlerhood

Fifty-six mothers and their 24-month-old toddlers were observed on two occasions in a series of laboratory procedures designed to assess relations between emotional functioning (emotional reactivity and emotion regulation) in an individual assessment and social behavior with a same-sex peer. Emotional reactivity was assessed using two frustration tasks designed to elicit distress. Emotional regulation was assessed by examining the child's behaviors (venting, distraction, focal-object focus, self-orientation, and mother-orientation) when confronted by the two distress-eliciting tasks. Peer play behaviors were coded for social participation and peer-directed conflict (aggressive) behavior. The results indicated that both emotional reactivity and emotion regulation were important predictors of at least two types of social behavior: conflict and cooperation. Distress to frustration, when accompanied by high venting or high focal-object focus, was significantly related to conflict with peers but not when accompanied by distraction, mother-orientation or self-focused behaviors. These findings are discussed in terms of the adaptive value of emotion regulation skills in early development, and the importance of identifying the causal relations between child regulation and early social competence.     

Structured measurement error in nutritional epidemiology: applications in the Pregnancy, Infection, and Nutrition (PIN) Study

Preterm birth, defined as delivery before 37 completed weeks' gestation, is a leading cause of infant morbidity and mortality. Identifying factors related to preterm delivery is an important goal of public health professionals who wish to identify etiologic pathways to target for prevention. Validation studies are often conducted in nutritional epidemiology in order to study measurement error in instruments that are generally less invasive or less expensive than "gold standard" instruments. Data from such studies are then used in adjusting estimates based on the full study sample. However, measurement error in nutritional epidemiology has recently been shown to be complicated by correlated error structures in the study-wide and validation instruments. Investigators of a study of preterm birth and dietary intake designed a validation study to assess measurement error in a food frequency questionnaire (FFQ) administered during pregnancy and with the secondary goal of assessing whether a single administration of the FFQ could be used to describe intake over the relatively short pregnancy period, in which energy intake typically increases. Here, we describe a likelihood-based method via Markov Chain Monte Carlo to estimate the regression coefficients in a generalized linear model relating preterm birth to covariates, where one of the covariates is measured with error and the multivariate measurement error model has correlated errors among contemporaneous instruments (i.e. FFQs, 24-hour recalls, and/or biomarkers). Because of constraints on the covariance parameters in our likelihood, identifiability for all the variance and covariance parameters is not guaranteed and, therefore, we derive the necessary and suficient conditions to identify the variance and covariance parameters under our measurement error model and assumptions. We investigate the sensitivity of our likelihood-based model to distributional assumptions placed on the true folate intake by employing semi-parametric Bayesian methods through the mixture of Dirichlet process priors framework. We exemplify our methods in a recent prospective cohort study of risk factors for preterm birth. We use long-term folate as our error-prone predictor of interest, the food-frequency questionnaire (FFQ) and 24-hour recall as two biased instruments, and serum folate biomarker as the unbiased instrument. We found that folate intake, as measured by the FFQ, led to a conservative estimate of the estimated odds ratio of preterm birth (0.76) when compared to the odds ratio estimate from our likelihood-based approach, which adjusts for the measurement error (0.63). We found that our parametric model led to similar conclusions to the semi-parametric Bayesian model.     

A hierarchical theory of occupational segregation and wage discrimination

Becker's model of discrimination is extended to the case where men exhibit distastes for working under female managers. The distribution of women in the resulting occupational hierarchy depends on the number of women in lower occupations, the wages of male workers in lower occupations, and male distastes for female management. Thus, there exists an occupational sorting function, related to wages, that determines the occupational distribution of women. We integrate this sorting function into a standard wage equation to derive a new decomposition of male-female wage differentials and apply it to a sample of insurance industry workers from the 1988 CPS.     

The Timing of Cohabitation and Engagement: Impact on First and Second Marriages

Using a multistate sample of marriages that took place in the 1990s, this study examined associations between premarital cohabitation history and marital quality in first (N = 437) and second marriages (N = 200) and marital instability in first marriages (intact N = 521, divorced N = 124). For first marriages, cohabiting with the spouse without first being engaged or married was associated with more negative interaction, higher self‐reported divorce proneness, and a greater probability of divorce compared to cohabiting after engagement or marriage (with patterns in the same direction for marital positivity). In contrast, there was a general risk associated with premarital cohabitation for second marriages on self‐reported indices of marital quality, with or without engagement when cohabitation began.     

The Virtuality of Virtual Worlds,or What We Can Learn from Playacting Horse Girls and Marginalized Developers

This article discusses the emergence of Habbo Hotel as a large‐scale virtual world and its changing versions through time. We consider how social events taking place within the hotel are conditioned by designed‐in symbolic resources and how, in turn, with creative processes of symbolization, novel social objects emerge out of particular interactions. We then discuss how the membership trajectories of hotel members are essential in understanding how these interactions are shaped and evolve. We also look at how the digital infrastructure and its evolution lends itself to being material for actualizing particular social worlds within the hotel and how the trajectory of the infrastructure reflects the relationship between the user and the developer communities of Habbo. Finally, we discuss why, to understand more fully what virtual worlds consist of at large, analysts should look into the mutually constitutive interactions among users, developers, and surrounding business models over longer periods of time in the constantly varying actualization of any given virtual world.     

Risk Prediction for Prostate Cancer Recurrence Through Regularized Estimation with Simultaneous Adjustment for Nonlinear Clinical Effects

In biomedical studies, it is of substantial interest to develop risk prediction scores using high-dimensional data such as gene expression data for clinical endpoints that are subject to censoring. In the presence of well-established clinical risk factors, investigators often prefer a procedure that also adjusts for these clinical variables. While accelerated failure time (AFT) models are a useful tool for the analysis of censored outcome data, it assumes that covariate effects on the logarithm of time-to-event are linear, which is often unrealistic in practice. We propose to build risk prediction scores through regularized rank estimation in partly linear AFT models, where high-dimensional data such as gene expression data are modeled linearly and important clinical variables are modeled nonlinearly using penalized regression splines. We show through simulation studies that our model has better operating characteristics compared to several existing models. In particular, we show that there is a non-negligible effect on prediction as well as feature selection when nonlinear clinical effects are misspecified as linear. This work is motivated by a recent prostate cancer study, where investigators collected gene expression data along with established prognostic clinical variables and the primary endpoint is time to prostate cancer recurrence. We analyzed the prostate cancer data and evaluated prediction performance of several models based on the extended c statistic for censored data, showing that 1) the relationship between the clinical variable, prostate specific antigen, and the prostate cancer recurrence is likely nonlinear, i.e., the time to recurrence decreases as PSA increases and it starts to level off when PSA becomes greater than 11; 2) correct specification of this nonlinear effect improves performance in prediction and feature selection; and 3) addition of gene expression data does not seem to further improve the performance of the resultant risk prediction scores.