Neither ‘family’ nor ‘corporate’ farming: Australian tomato growers as farm family entrepreneurs

For the past two decades there has been much debate about the future of family farming. The basic question on which this debate has turned is whether current pressures on family farm systems should be understood as symptomatic of a terminal condition, in which farmers are replaced progressively by corporate ownership; or whether family farms will persist as a social formation, albeit increasingly subsumed by off-farm interests. Using evidence from the Australian processing tomato sector, this article documents the changing social and economic formation of ‘family farming’. We argue that in this industry, the appropriate way to describe farmers is through the deployment of that a new category of farming; farm family entrepreneurs. This phrase is coined to describe the situation where family units remain at the social and economic heart of farm ownership and operation, but in the context where they relate to their land-based assets through legal and financial structures characteristic of the wider economy. As this article explores, this formation seems to represent an accommodating modus operandi for farm units within neo-liberal agricultural governance. Nevertheless, however, this duality of family-based structures and capitalist entrepreneurialism inevitably provokes a series of tensions, whose resolution requires a variety of organizational strategies to be put in place.     

Assessing reoffense risk with juvenile sexual offenders

This article summarizes a two-year study of juvenile sexual offenders in Washington. Both community-based and institution-based treatment programs were evaluated. A typical profile of the juvenile sexual offender is offered, as well as recidivism data from a mean 20-month follow-up period.     

The transition to parenthood in Puerto Rico: Occupational status and the timing of first births

This study examines the relationship between occupational status and fertility timing during a period of rapid development in Puerto Rico. Our fundamental hypothesis is that women with higher status occupations face greater opportunity costs than those with less valued jobs and therefore will be more likely to postpone parenthood until later ages than women without such high costs. We test this hypothesis using event history techniques with data from the 1982 Puerto Rico Fertility and Family Planning Assessment, an island-wide survey of women between the ages of 15 and 49. The analysis examines the effects of occupational status on the timing of first births, and finds strong support for the basic hypothesis, especially regarding the post-ponement of teen births. After the teen years, the effects are less pronounced. Overall, it appears that employment opportunities have played an important role in childbearing decisions in Puerto Rico.An earlier version of this paper was presented at the annual meeting of the Population Association of America, Denver, Colorado, 30 April–2 May 1992.     

The Expression of Victory and Loss: Estimating Who’s Leading or Trailing from Nonverbal Cues in Sports

The goal of the paper was to test if humans can detect whether athletes are trailing or leading in sports based on the perception of thin slices of athletes’ nonverbal behavior. In Experiment 1, participants who were unexperienced in the respective sports watched short videos depicting basketball and table tennis players and rated whether athletes were trailing or leading. Results indicated that participants could significantly differentiate between trailing and leading athletes in both team and individual sports. Experiment 2 showed that children were also able to distinguish between trailing and leading athletes based on nonverbal behavior. Comparison with the adult results from Experiment 1 revealed that the adult ratings corresponded to a higher degree with the actual scores during the game compared to the children’s. In Experiment 3, we replicated the findings from Experiment 1 with both expert and unexperienced participants and a different set of stimuli from team handball. Both experts and unexpert participants were able to differentiate between leading and trailing athletes. Our findings are in line with evolutionary accounts of nonverbal behavior and suggest that humans display nonverbal signals as a consequence of leading or trailing which are reliably interpreted by others. By comparing this effect as a function of different age groups we provide evidence that although even young children can differentiate between leading and trailing athletes, the decoding of subtle nonverbal cues continues to develop with increasing experience and maturation processes.     

Videogame Assisted Emotional Regulation Training: An ACT with RAGE-Control Case Illustration

This paper describes the treatment of an adolescent girl (age 16) who received the ACT with RAGE-Control intervention during her treatment in an urban inpatient psychiatry unit. ACT with RAGE-Control utilizes five traditional Cognitive Behavioral techniques combined with an active biofeedback videogame designed to strengthen a patient’s self-regulatory capacities while facing simulated stress in a virtual environment. The treatment is delivered as daily individual psychotherapy sessions over five consecutive days of an inpatient psychiatric admission. The following case illustrates the theory and techniques of the ACT with RAGE-Control intervention.     

Mini-batch learning of exponential family finite mixture models

Mini-batch algorithms have become increasingly popular due to the requirement for solving optimization problems, based on large-scale data sets. Using an existing online expectation–maximization (EM) algorithm framework, we demonstrate how mini-batch (MB) algorithms may be constructed, and propose a scheme for the stochastic stabilization of the constructed mini-batch algorithms. Theoretical results regarding the convergence of the mini-batch EM algorithms are presented. We then demonstrate how the mini-batch framework may be applied to conduct maximum likelihood (ML) estimation of mixtures of exponential family distributions, with emphasis on ML estimation for mixtures of normal distributions. Via a simulation study, we demonstrate that the mini-batch algorithm for mixtures of normal distributions can outperform the standard EM algorithm. Further evidence of the performance of the mini-batch framework is provided via an application to the famous MNIST data set.