Early childhood education and crime

This article presents new evidence on the crime-reducing impacts of a high-quality, intensive early childhood program with long-term follow-up, evaluated by a randomized controlled trial. Proportionately, more women than men decrease their criminal activity after participating in the program. This gender difference arises because of the worse home environments for girls, with corresponding greater scope for improvement by the program. For both genders, treatment effects are larger for the least-advantaged children, as measured by their mother's education at baseline. The dollar value of the social cost of criminal activity averted is higher for men because they commit more costly violent crimes.     

The number 747 is named faster after seeing Boeing than after seeing Levi's: Associative priming in the processing of multidigit Arabic numerals

Two experiments are reported in which naming multidigit Arabic numerals was shown to depend on the context in which the numbers were presented. Number naming and number decisions were faster after an associative prime (e.g., 747 preceded by the word Boeing) than after an unre- lated prime, both in unmasked and masked priming conditions. On the basis of these findings, we conclude that number naming is not always based on a quantity-based semantically mediated pathway.     

The dynamics of work-family relationships in managerial lives

This article will focus on the relationship between professional and private life among successful managers, people who live outwardly meaningful work lives. We wish to report some findings from a broader study, showing the dynamic nature of this relationship which changes during the course of adult life. The latter part of the paper assesses those dynamics and their implications.     

A Latent Block Distance-Association Model for Profile by Profile Cross-Classified Categorical Data

Abstract

Distance association models constitute a useful tool for the analysis and graphical representation of cross-classified data in which distances between points inversely describe the association between two categorical variables. When the number of cells is large and the data counts result in sparse tables, the combination of clustering and representation reduces the number of parameters to be estimated and facilitates interpretation. In this article, a latent block distance-association model is proposed to apply block clustering to the outcomes of two categorical variables while the cluster centers are represented in a low dimensional space in terms of a distance-association model. This model is particularly useful for contingency tables in which both the rows and the columns are characterized as profiles of sets of response variables. The parameters are estimated under a Poisson sampling scheme using a generalized EM algorithm. The performance of the model is tested in a Monte Carlo experiment, and an empirical data set is analyzed to illustrate the model.