On the Marriageability of Men

The “marriageability of men” is an argument used in sociological research to understand demographic changes in marriage and to analyze social dynamics associated with gender, race, class, family, the workplace, incarceration, and more. While some are marrying later and others are foregoing marriage altogether, a lack of marriageable men is often part of the argument concerning new patterns of family formation in the United States. Research mobilizing the marriageability of men hypothesis spans a great deal of subfields of sociological research, not all in conversation with one another – and not all explicitly making use of the term. This article collects these diverse strands of thought and presents an argument for how and why men are less marriageable, what this means, and why it means different things for different groups of men and women. Racialized and classed conceptions of masculinity create different kinds of struggles for different groups of men and work against their marriageability for different reasons. We discuss the impact of incarceration, new struggles in a service economy, and shifts in women's perceptions and expectations of what qualifies men as “marriageable.”     

Measuring Sharedness of Team-Related Knowledge: Design and Validation of a Shared Mental Model Instrument

Many researchers have explored how people share and construct similar mental models in teams. They have claimed that successful team performance depends on a shared mental model of team members about task, team, equipment and situation. Most of the literature has illustrated simplified relationships between a team's mental model and their performance without a valid instrument addressing the confined and relevant constructs of a shared mental model. This paper describes the instrument development steps and the conceptual framework for factors associated with shared mental models. After development and refinement, the instrument was finalized for use to measure team-related knowledge. The final instrument consists of 42 items that are linked to the five emergent factors of shared mental models including general task and team knowledge, general task and communication skills, attitude toward teammates and task, team dynamics and interactions, and team resources and working environment.     

On the robustness of the generalized fused lasso to prior specifications

Using networks as prior knowledge to guide model selection is a way to reach structured sparsity. In particular, the fused lasso that was originally designed to penalize differences of coefficients corresponding to successive features has been generalized to handle features whose effects are structured according to a given network. As any prior information, the network provided in the penalty may contain misleading edges that connect coefficients whose difference is not zero, and the extent to which the performance of the method depend on the suitability of the graph has never been clearly assessed. In this work we investigate the theoretical and empirical properties of the adaptive generalized fused lasso in the context of generalized linear models. In the fixed \(p\) setting, we show that, asymptotically, adding misleading edges in the graph does not prevent the adaptive generalized fused lasso from enjoying asymptotic oracle properties, while forgetting suitable edges can be more problematic. These theoretical results are complemented by an extensive simulation study that assesses the robustness of the adaptive generalized fused lasso against misspecification of the network as well as its applicability when theoretical coefficients are not exactly equal. Our contribution is also to evaluate the applicability of the generalized fused lasso for the joint modeling of multiple sparse regression functions. Illustrations are provided on two real data examples.     

Clinical and Supervisory Considerations for Transgender Therapists: Implications for Working with Clients

Transgender therapists have unique and valuable perspectives into how gender organizes the therapeutic process. Currently, in the MFT field, there is discussion of the cisgender therapist's experience in the therapy room, but no known articles on the transgender therapist's experience. This article provides insight into the experiences of transgender therapists around issues of self‐disclosure, social locations of both therapist and client, and clinical supervision. Drawing from our clinical experiences as transmen, we highlight special considerations for working with cisgender, queer, and transgender clients. Implications for supervision of transgender therapists are also discussed. As more gender diverse students seek MFT training, there is an urgent need to acknowledge their perspectives. This article is a call for beginning conversations in this direction.     

Cognitive skills and leadership performance: The nine critical skills

Over the years, a growing body of evidence indicates that certain cognitive skills are a critical determinant of leader performance. In the present effort we show that application of these skills is typically founded in case-based knowledge. Subsequently, we identify nine key skills people in leadership positions employ when working with case-based knowledge to address leadership problems: 1) problem definition, 2) cause/goal analysis, 3) constraint analysis, 4) planning, 5) forecasting, 6) creative thinking, 7) idea evaluation, 8) wisdom, and 9) sensemaking/visioning. Individual and situational contingencies shaping effective application of these thinking skills is discussed. In addition, the implications of findings bearing on leader thinking skills for leader assessment and leader development are considered.     

The Immigrant Paradox in Pregnancy: Explaining the First‐Generation Advantage for Latina Adolescents

The immigrant paradox is a population health pattern whereby later generation immigrant youth display less favorable outcomes when compared to first‐generation co‐ethnic peers. This study examines the role of number of sex partners in explaining the immigrant paradox in pregnancy among Latina adolescents. This secondary analysis utilized a nationally representative sample of Latinas in the National Longitudinal Study of Adolescent Health. As expected, first‐generation Latina adolescents demonstrated less risk than second‐ or third+ generation Latinas for becoming pregnant. Further, the lower number of sexual partners fully accounted for the first generation's advantage in lower rate of adolescent pregnancy. These findings have important implications for healthcare providers who work with Latina girls in pregnancy prevention.     

A mixture model for random graphs

The Erdös–Rényi model of a network is simple and possesses many explicit expressions for average and asymptotic properties, but it does not fit well to real-world networks. The vertices of those networks are often structured in unknown classes (functionally related proteins or social communities) with different connectivity properties. The stochastic block structures model was proposed for this purpose in the context of social sciences, using a Bayesian approach. We consider the same model in a frequentest statistical framework. We give the degree distribution and the clustering coefficient associated with this model, a variational method to estimate its parameters and a model selection criterion to select the number of classes. This estimation procedure allows us to deal with large networks containing thousands of vertices. The method is used to uncover the modular structure of a network of enzymatic reactions.     

Semiparametric multiple kernel estimators and model diagnostics for count regression functions

Abstract

This study concerns semiparametric approaches to estimate discrete multivariate count regression functions. The semiparametric approaches investigated consist of combining discrete multivariate nonparametric kernel and parametric estimations such that (i) a prior knowledge of the conditional distribution of model response may be incorporated and (ii) the bias of the traditional nonparametric kernel regression estimator of Nadaraya-Watson may be reduced. We are precisely interested in combination of the two estimations approaches with some asymptotic properties of the resulting estimators. Asymptotic normality results were showed for nonparametric correction terms of parametric start function of the estimators. The performance of discrete semiparametric multivariate kernel estimators studied is illustrated using simulations and real count data. In addition, diagnostic checks are performed to test the adequacy of the parametric start model to the true discrete regression model. Finally, using discrete semiparametric multivariate kernel estimators provides a bias reduction when the parametric multivariate regression model used as start regression function belongs to a neighborhood of the true regression model.