Do Iconic Hand Gestures Really Contribute to the Communication of Semantic Information in a Face-to-Face Context?

Previous research has shown that iconic gestures are effective at communicating semantic information, particularly about the size and relative position of objects. However, the conclusions of these experiments have been somewhat limited by the fact that the methodology has typically involved presenting gesture–speech samples on video rather than in an actual face-to-face context. Because these different viewing conditions can impact on addressees’ behavior and perception, and therefore potentially impact on the amount of information they receive from gestures, the present study compares the communicative effectiveness of iconic gestures when viewed in a face-to-face context compared to when viewed on video. The results are quite striking in that gestures seemed at least as effective, and in some cases even more effective at communicating position and size information when they occurred in the face-to-face condition compared to video.     

Risk of Antibiotic-Resistant Staphylococcus aureus Dispersion from Hog Farms: A Critical Review

The World Health Organization has declared antibiotic resistance “one of the biggest threats to global health.” Mounting evidence suggests that antibiotic use in industrial-scale hog farming is contributing to the spread of antibiotic-resistant Staphylococcus aureus. To capture available evidence on these risks, we searched peer-reviewed studies published before June 2017 and conducted a meta-analysis of these studies’ estimates of the prevalence of swine-associated, antibiotic-resistant S. aureus in animals, humans, and the environment. The 166 relevant studies revealed consistent evidence of livestock-associated methicillin-resistant S. aureus (MRSA) in hog herds (55.3%) raised with antibiotics. MRSA prevalence was also substantial in slaughterhouse pigs (30.4%), industrial hog operation workers (24.4%), and veterinarians (16.8%). The prevalence of swine-associated, multidrug-resistant S. aureus (MDRSA)—with resistance to three or more antibiotics—is not as well documented. Nonetheless, sufficient studies were available to estimate MDRSA pooled prevalence in conventional hog operation workers (15.0%), workers’ household members (13.0%), and community members (5.37%). Evidence also suggests that antibiotic-resistant S. aureus can be present in air, soil, water, and household surface samples gathered in or near high-intensity hog operations. An important caveat is that prevalence estimates for humans reflect colonization, not active infection, and the health risks of colonization remain poorly understood. In addition, these pooled results may not represent risks in specific locations, due to wide geographic variation. Nonetheless, these results underscore the need for additional preventive action to stem the spread of antibiotic-resistant pathogens from livestock operations and a streamlined reporting system to track this risk.     

Collaborative Family Work in Youth Justice

ABSTRACT

A number of studies have found that working with family groups can be successful in improving outcomes for young people and their families. This article reports on a study in New South Wales in which juvenile justice staff offered collaborative family work interventions to young people as part of the routine offerings of a juvenile justice service. The primary objective of this study was to examine the extent to which young people who completed the family work had lower recidivism rates compared to three control groups. The methods included a comparison of recidivism rates between young people who completed the intervention, those who failed to complete, those who declined, and a matched sample of young people who were not offered the intervention. The results of the study indicated that many young people and their families were agreeable to be involved in the intervention and the completion rates were high, particularly if the work was undertaken in the family home. The young people who completed the intervention also had lower recidivism rates than young people in each of the control groups.

IMPLICATIONS

• Collaborative family work can be offered successfully by juvenile justice services to young offenders and their families.

• Collaborative family work can reduce recidivism rates for those who complete the intervention.

• It is preferable to conduct the work in the family home where completion rates are likely to be higher.

     

An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified

There has been increasing interest in using semi-supervised learning to form a classifier. As is well known, the (Fisher) information in an unclassified feature with unknown class label is less (considerably less for weakly separated classes) than that of a classified feature which has known class label. Hence in the case where the absence of class labels does not depend on the data, the expected error rate of a classifier formed from the classified and unclassified features in a partially classified sample is greater than that if the sample were completely classified. We propose to treat the labels of the unclassified features as missing data and to introduce a framework for their missingness as in the pioneering work of Rubin (Biometrika 63:581–592, 1976) for missingness in incomplete data analysis. An examination of several partially classified data sets in the literature suggests that the unclassified features are not occurring at random in the feature space, but rather tend to be concentrated in regions of relatively high entropy. It suggests that the missingness of the labels of the features can be modelled by representing the conditional probability of a missing label for a feature via the logistic model with covariate depending on the entropy of the feature or an appropriate proxy for it. We consider here the case of two normal classes with a common covariance matrix where for computational convenience the square of the discriminant function is used as the covariate in the logistic model in place of the negative log entropy. Rather paradoxically, we show that the classifier so formed from the partially classified sample may have smaller expected error rate than that if the sample were completely classified.