PARENTS BEYOND CONFLICT WORKSHOP

This article reviews a program designed in response to high-conflict parents who have protracted family law cases and have been referred to dependency court due to child abuse allegations.     

Patterns of Young Adult Social Roles Transitions Across 24 Months and Subsequent Substance Use and Mental Health

Journal of Youth and Adolescence - Young adults experience social role transitions across multiple life domains, and a deeper understanding of the ways in which these simultaneous transition...     

Silencing Women's Voices: Nuisance Property Laws and Battered Women

There is little documentation about how nuisance property laws, which fine people for excessive 911 calls, affect victims of domestic violence. In St. Louis, we found that police and prosecutors believe that the law benefits victims of domestic violence by providing them with additional services. By contrast, advocates for domestic violence victims believe that the law undermines battered women's access to housing and discourages them from calling 911. Using qualitative data, we analyze how the organizational structures and dynamics within which each group works give rise to different stocks of working knowledge. We conclude that law enforcement officials are unaware of these harms because women's voices and experiences are marginalized during the enforcement process. This research reveals mechanisms through which law enforcement policies reinforce gender inequality, and illustrates some ways in which gender relations and power come into play in what, on their surface, appear to be gender‐neutral laws.     

Does gang membership pay? Illegal and legal earnings through emerging adulthood*

Gang membership is believed to impede success in the legitimate economic market while simultaneously supporting success in the illegal market. We extend the study of the economic effects of gang membership by using a within‐ and between‐individual analytic design, decomposing gang membership into multiple statuses (i.e., entering a gang, continuously in a gang, leaving a gang, and inactive gang membership), examining legal and illegal earnings simultaneously, and accounting for factors endogenous to gang membership that may contribute to economic achievement. By using panel data from 1,213 individuals who participated in the Pathways to Desistance Study to conduct a multilevel path analysis, we find that active gang membership status is unrelated to legal earnings. Alternatively, entering a gang is associated with increased illegal earnings, attributable to changes in delinquent peers and drug use, whereas leaving a gang has a direct relationship with decreased illegal earnings. Our results indicate that the positive economic effect of gang membership (i.e., illegal earnings and total earnings) is short‐lived and that, on balance, the sum of the gang membership experience does not “pay” in terms of overall earnings.     

Identification of Eight Synthetic Cannabinoids,Including 5F‐AKB48 in Seized Herbal Products Using DART‐TOF‐MS and LC‐QTOF‐MS as Nontargeted Screening Methods

Synthetic cannabinoids are sprayed onto plant material and smoked for their marijuana‐like effects. Clandestine manufacturers modify synthetic cannabinoid structures by creating closely related analogs. Forensic laboratories are tasked with detection of these analog compounds, but targeted analytical methods are often thwarted by the structural modifications. Here, direct analysis in real time coupled to accurate mass time‐of‐flight mass spectrometry (DART‐TOF‐MS) in combination with liquid chromatography quadruple time‐of‐flight mass spectrometry (LC‐QTOF‐MS) are presented as a screening and nontargeted confirmation method, respectively. Methanol extracts of herbal material were run using both methods. Spectral data from four different herbal products were evaluated by comparing fragmentation pattern, accurate mass and retention time to available reference standards. JWH‐018, JWH‐019, AM2201, JWH‐122, 5F‐AKB48, AKB48‐N‐(4‐pentenyl) analog, UR144, and XLR11 were identified in the products. Results demonstrate that DART‐TOF‐MS affords a useful approach for rapid screening of herbal products for the presence and identification of synthetic cannabinoids.     

Patella sex determination by 3D statistical shape models and nonlinear classifiers

Sex determination is one of the essential steps in personal identification of an individual from skeletal remains. Most elements of the skeleton have been subjected to discriminant function analysis for sex estimation, but little work has been done in terms of the patella. This paper proposes a new sex determination method from the patella using a novel automated feature extraction technique. A dataset of 228 patellae (95 females and 133 males) was amassed from the William M. Bass Donated Skeletal Collection from the University of Tennessee and was subjected to noninvasive high resolution computed tomography (CT). After the CT data were segmented, a set of features was automatically extracted, normalized, and ranked. The segmentation process with surface smoothing minimizes the noise from enthesophytes and ultimately allows our methods to distinguish variations in patellar morphology. These features include geometric features, moments, principal axes, and principal components. A feature vector of dimension 45 for each subject was then constructed. A set of statistical and supervised neural network classification methods were used to classify the sex of the patellar feature vectors. Nonlinear classifiers such as neural networks have been used in previous research to analyze several medical diagnosis problems, including quantitative tissue characterization and automated chromosome classification. In this paper, different classification methods were compared. Classification success ranged from 83.77% average classification rate using labels from a Fuzzy C-Means (FCM) clustering step, to 90.3% for linear discriminant classification (LDC). We obtained results of 96.02% and 93.51% training and testing classification rates, respectively, using feed-forward backpropagation neural networks (NN). These promising results using newly developed features and the application of nonlinear classifiers encourage the usage of these methods in forensic anthropology for identifying the sex of an individual from incomplete skeletons retaining at least one patella.