A Holland Perspective on the U.S. Workforce From 1960 to 2000

The authors analyze civilian occupations and employment data collected by the U.S. Census Bureau in 1960, 1970, 1980, 1990, and 2000 with respect to 6 kinds of work (Holland's RIASEC [Realistic, Investigative, Artistic, Social, Enterprising, Conventional] classification), employment, and gender. For the 1990 and 2000 censuses, kinds of work, gender, and income are analyzed, and for the 2000 census, kinds of work, age, and gender are examined. Past employment trends developed from census data are further analyzed with respect to Bureau of Labor Statistics employment projections through 2012. Implications for further research, employment policy, and career services are offered.     

Adaptive wavelet estimation of a density from mixtures under multiplicative censoring

In this paper, a mixture model under multiplicative censoring is considered. We investigate the estimation of a component of the mixture (a density) from the observations. A new adaptive estimator based on wavelets and a hard thresholding rule is constructed for this problem. Under mild assumptions on the model, we study its asymptotic properties by determining an upper bound of the mean integrated squared error over a wide range of Besov balls. We prove that the obtained upper bound is sharp.     

The World Ozymandias Made: Utopias in the Superhero Comic,Subculture, and the Conservation of Difference

Revolution is the triumph of freedom; its organization is based on spontaneity, not on the dictates of a “hero” who imposes himself through violence. It is a continuous and systematic elevation of a people, following the lines of a hierarchy, and creating for itself one by one the organs that the new social life demands.     

On the Cycle-Transitivity of the Dice Model

We introduce the notion of a dice model as a framework for describing a class of probabilistic relations. We investigate the transitivity of the probabilistic relation generated by a dice model and prove that it is a special type of cycle-transitivity that is situated between moderate stochastic transitivity or product-transitivity on the one side, and ukasiewicz-transitivity on the other side. Finally, it is shown that any probabilistic relation with rational elements on a three-dimensional space of alternatives which possesses this particular type of cycle-transitivity, can be represented by a dice model. The same does not hold in higher dimensions.     

Spatial Patterns of Fertility Transition in Indian Districts

The article explores the dynamics of Indian fertility at the district level using a child‐woman index developed from the four Indian censuses, 1961 to 1991. It employs statistical and geostatistical techniques to assess fertility change across districts and periods. Fertility decline is evident in every region, but sizable regional differentials exist. A cluster analysis of fertility profiles indicates that a clear spatial pattern of fertility in India has emerged and the pattern intensified because of the process of fertility decline.     

Who Gets Custody Now? Dramatic Changes in Children’s Living Arrangements After Divorce

This article reexamines the living arrangements of children following their parents’ divorce, using Wisconsin Court Records, updating an analysis that showed relatively small but significant increases in shared custody in the late 1980s and early 1990s. These changes have accelerated markedly in the intervening years: between 1988 and 2008, the proportion of mothers granted sole physical custody fell substantially, the proportion of parents sharing custody increased dramatically, and father–sole custody remained relatively stable. We explore changes in the correlates of alternative custody outcomes, showing that some results from the earlier analysis still hold (for example, cases with higher total family income are more likely to have shared custody), but other differences have lessened (shared-custody cases have become less distinctive as they have become more common). Despite the considerable changes in marriage and divorce patterns over this period, we do not find strong evidence that the changes in custody are related to changes in the characteristics of families experiencing a divorce; rather, changes in custody may be the result of changes in social norms and the process by which custody is determined.     

Fathers’ Imprisonment and Mothers’ Multiple-Partner Fertility

We consider the intersection between two striking U.S. trends: dramatic increases in the imprisonment of fathers and increases in the proportion of mothers who have children with more than one partner (multiple-partner fertility, or MPF). Using matched longitudinal administrative data that provide unusually comprehensive and accurate information about the occurrence and timing of imprisonment, fertility, and MPF for the population of the state of Wisconsin, we consider the relationship between paternal imprisonment and MPF among unwed mothers. Employing discrete-time event history analysis with multinomial logistic regression, we model the occurrence and timing of the mother’s second birth, distinguishing between a birth with the same father and a birth with a different father, and distinguishing between current imprisonment and a history of imprisonment. We find that current imprisonment is associated with an increased likelihood of MPF and a decreased likelihood of fertility with the same father (compared with no additional birth) and that a history of imprisonment is associated with increased MPF in some models but not in our preferred model. To control for unobserved heterogeneity among mothers and assess the evidence of a causal effect of fathers’ imprisonment, we also employ the case-time-control method, a fixed-effects method for the analysis of nonrepeated events. Results suggest that fathers’ current imprisonment may increase mothers’ MPF. Policy implications are discussed.     

Stable and visualizable Gaussian parsimonious clustering models

Gaussian mixture model-based clustering is now a standard tool to determine a hypothetical underlying structure in continuous data. However, many usual parsimonious models, despite either their appealing geometrical interpretation or their ability to deal with high dimensional data, suffer from major drawbacks due to scale dependence or unsustainability of the constraints after projection. In this work we present a new family of parsimonious Gaussian models based on a variance-correlation decomposition of the covariance matrices. These new models are stable when projected into the canonical planes and, so, faithfully representable in low dimension. They are also stable by modification of the measurement units of the data and such a modification does not change the model selection based on likelihood criteria. We highlight all these stability properties by a specific graphical representation of each model. A detailed Generalized EM (GEM) algorithm is also provided for every model inference. Then, on biological and geological data, we compare our stable models to standard ones (geometrical models and factor analyzer models), which underlines all the profit to obtain unit-free models.     

A tutorial on adaptive MCMC

We review adaptive Markov chain Monte Carlo algorithms (MCMC) as a mean to optimise their performance. Using simple toy examples we review their theoretical underpinnings, and in particular show why adaptive MCMC algorithms might fail when some fundamental properties are not satisfied. This leads to guidelines concerning the design of correct algorithms. We then review criteria and the useful framework of stochastic approximation, which allows one to systematically optimise generally used criteria, but also analyse the properties of adaptive MCMC algorithms. We then propose a series of novel adaptive algorithms which prove to be robust and reliable in practice. These algorithms are applied to artificial and high dimensional scenarios, but also to the classic mine disaster dataset inference problem.