Mexican American birthweight and child overweight: unraveling a possible early life course health transition

Mexican American children have a weight distribution that categorizes them as relatively healthy at birth but relatively unhealthy by age 3. This early life course transition in health based on weight raises the question of whether Mexican American children "outgrow" the epidemiologic paradox of favorable birth outcomes despite social disadvantage or whether their birthweight distribution places them on trajectory for overweight in childhood. We address this question using newly available 9-year follow-up data from the Fragile Families and Child Wellbeing birth cohort study linked to pre-natal medical records. We systematically investigate the roles of birthweight, pre-natal factors, and childhood factors in explaining racial/ethnic differences in childhood overweight. Our main finding is that Mexican American children do outgrow the paradox: Their rates of childhood overweight are higher than expected given their birthweight distribution. Observed pre-natal and childhood factors do not explain the elevated rates of overweight among Mexican American children.     

Why the Extractive Industry Should Support Mandatory Transparency: A Shared Value Approach

The Transparency Amendment, included in the Dodd‐Frank Wall Street Reform and Consumer Protection Act, can be an important tool in curtailing the resource curse that so heavily burdens resource‐rich developing countries by shedding light on opaque payments between the extractive sector and host countries. From the get‐go, however, extractive industry companies have fiercely opposed the new mandatory disclosure requirements as set out in this regulation. The corporate opposition is for the largest part motivated by the fear of a competitive disadvantage that derives from the fact that the amendment is housed with the Securities and Exchange Commission (SEC) and thus only holds jurisdiction over those that report to the SEC. Although on the one hand watering down these corporate fears, this article draws on the “shared value approach” and empirical evidence to argue that there is a business case for transparency. This refreshing take on transparency regulation invites corporate leaders to reassess their current oppositional stance and to embrace new initiatives like the Transparency Amendment and to take a proactive stance in building a convincing global regulatory system of transparency.     

Sequential design of computer experiments for the estimation of a probability of failure

This paper deals with the problem of estimating the volume of the excursion set of a function f:ℝ ^d →ℝ above a given threshold, under a probability measure on ℝ ^d that is assumed to be known. In the industrial world, this corresponds to the problem of estimating a probability of failure of a system. When only an expensive-to-simulate model of the system is available, the budget for simulations is usually severely limited and therefore classical Monte Carlo methods ought to be avoided. One of the main contributions of this article is to derive SUR (stepwise uncertainty reduction) strategies from a Bayesian formulation of the problem of estimating a probability of failure. These sequential strategies use a Gaussian process model of f and aim at performing evaluations of f as efficiently as possible to infer the value of the probability of failure. We compare these strategies to other strategies also based on a Gaussian process model for estimating a probability of failure.     

Piecewise deterministic Markov processes applied to fatigue crack growth modelling

In this paper, we use a particular piecewise deterministic Markov process (PDMP) to model the evolution of a degradation mechanism that may arise in various structural components, namely, the fatigue crack growth. We first derive some probability results on the stochastic dynamics with the help of Markov renewal theory: a closed-form solution for the transition function of the PDMP is given. Then, we investigate some methods to estimate the parameters of the dynamical system, involving Bogolyubov's averaging principle and maximum likelihood estimation for the infinitesimal generator of the underlying jump Markov process. Numerical applications on a real crack data set are given.     

Effects of Welfare Participation on Marriage

We investigate the widely held premise that welfare participation causes women to refrain from marriage. Using data from the Fragile Families and Child Wellbeing study (N = 3,219), we employ an event history approach to study transitions to marriage among mothers who have had a non-marital birth. We find that welfare participation reduces the likelihood of transitioning to marriage (hazard ratio is .67, p < .01), but only while the mother is receiving benefits. Once the mother leaves welfare, past receipt has little effect on marriage. We infer that the negative association between welfare participation and subsequent marriage reflects temporary economic disincentives rather than an erosion of values.     

Cyclical Cohabitation Among Unmarried Parents in Fragile Families

Building on past research suggesting that cohabitation is an ambiguous family form, the authors examined an understudied residential pattern among unmarried parents: cyclical cohabitation, in which parents have multiple cohabitation spells with each other. Using 9 years of panel data from the Fragile Families and Child Wellbeing Study (N = 2,084), they found that 10% of all parents with nonmarital births and nearly a quarter of those living together when the child is 9 years old are cyclical cohabitors. Cyclically cohabiting mothers reported more material hardships than mothers in most other relationship patterns but also reported more father involvement with children. On all measures of child well‐being except grade retention, children of cyclically cohabiting parents fared no worse than children of stably cohabiting biological parents and did not differ significantly from any other group.     

A ‘Minority’ on the Move: Boundary Work among Filipina Muslim Migrant Domestic Workers in the Middle East

This article analyses the migration of a religious ‘minority’ that is largely invisible within migration studies, namely Muslim Filipina domestic workers. More specifically, this research shows that the category of ‘minority’ is not fixed and is always negotiated through transnational spaces and boundary work. In doing so, the article highlights how religious belonging, the status of minority and migration intersect and are negotiated during the period prior to these women leaving their country, during their time in the country of destination, and when they return to the Philippines. How boundary work affects the religious belonging of this Muslim ‘minority’ is underlined by presenting the Middle East as an opportunity to perform norms of ‘Muslimness’. The performance of these norms as an opportunity for these women to challenge the status of being a ‘minority’ in the Philippines is also examined. Finally, this article shows how these Muslim ‘minorities’ gain access to a certain symbolic capital by becoming hajji and balikbayan (returnees) when they return home.     

Stories from the circle: Leadership lessons learned from aboriginal leaders

While much has been written about leadership, very little research has examined North American Aboriginal leadership. Drawing upon a qualitative methodology, our findings suggest several differences in how Aboriginal leaders view leadership; compared to non-Aboriginals or mainstream approaches to leadership. We found that Aboriginals view leadership as a spiritual endeavor that is holistic and egalitarian in nature. Aboriginal leaders use a more indirect style of communication that frequently invokes traditional imagery, story-telling and animal-based metaphors. Aboriginal leaders also draw from the Medicine Wheel as a guide. In conclusion, we discuss several challenges shared by Aboriginal leaders including the tall poppy syndrome and walking in two worlds and accordingly, offer managerial implications of our findings.     

School Engagement Trajectories and Their Differential Predictive Relations to Dropout

Although most theories draw upon the construct of school engagement in their conceptualization of the dropout process, research addressing its hypothesized prospective relation with dropout remains scarce and does not account for the academic and social heterogeneity of students who leave school prematurely. This study explores the reality of different life-course pathways of school engagement and their predictive relations to dropout. Using an accelerated longitudinal design, we used growth mixture modeling to generate seven distinct trajectories of school engagement with 12- to 16-year-old students (N = 13,300). A vast majority of students were classified into three stable trajectories, distinguishing themselves at moderate to very high levels of school engagement. We refer to these as developmentally normative pathways in light of their frequent occurrence and stability. Although regrouping only one-tenth of participants, four other nonnormative (or unexpected pathways) accounted for the vast majority of dropouts. Dropout risk was closely linked with unstable pathways of school engagement. We conclude by debating the delicate investment balance between universal strategies and more selective and differentiated strategies to prevent dropout. We also discuss the need to better understand why, within normative trajectories, some students with high levels of school engagement drop out of school .     

Adaptive sequential Monte Carlo by means of mixture of experts

Appropriately designing the proposal kernel of particle filters is an issue of significant importance, since a bad choice may lead to deterioration of the particle sample and, consequently, waste of computational power. In this paper we introduce a novel algorithm adaptively approximating the so-called optimal proposal kernel by a mixture of integrated curved exponential distributions with logistic weights. This family of distributions, referred to as mixtures of experts, is broad enough to be used in the presence of multi-modality or strongly skewed distributions. The mixtures are fitted, via online-EM methods, to the optimal kernel through minimisation of the Kullback-Leibler divergence between the auxiliary target and instrumental distributions of the particle filter. At each iteration of the particle filter, the algorithm is required to solve only a single optimisation problem for the whole particle sample, yielding an algorithm with only linear complexity. In addition, we illustrate in a simulation study how the method can be successfully applied to optimal filtering in nonlinear state-space models.