Effects of Africentric Socialization on Psychosocial Outcomes in Black Girls: The Critical Role of Gender

African American social work scholars recommend rigorous research and evaluation of Africentric interventions as one approach to building culturally appropriate, evidence-based treatments for the Black community. Following this approach, this pilot study evaluates the Imani Rites of Passage program, a 15-week Africentric curriculum with 10 Black adolescent females (mean age = 12.40), comparing their pre- and post-intervention data to that of a no-intervention group of 13 Black males (mean age = 12.08). The program evaluation is based on the degree of correspondence between theory and the measurement model spelled out by the cognitive-cultural view of African-American identity. The findings for Black females were consistent with the cognitive-cultural model in some ways but not in others, and they were more complex than the predictions. Future Africentric interventions guided by the cognitive-cultural model must consider gender differences in the outcomes. Implications for social work research and practice are discussed.     

Impact of Race on the Implementation of Empirically Supported Treatments in Substance Abuse Treatment

The effort to address the gap between research and practice in substance abuse treatment has largely neglected the role of local resources and political trends. This study seeks to clarify the role of the local environment in implementing empirically supported treatments (ESTs). The study consisted of secondary data analysis of substance abuse treatment centers (N = 13,079) and U.S. Census data to determine the likelihood of using EST by substance abuse treatment centers in counties with 50% or more Black residents. Bivariate and multivariate models were employed. After controlling for various factors, results indicate that substance use disorder treatment agencies that accept federal funding are less likely to use ESTs if they are located in counties with predominantly (> 50%) Black residents. Implementation of ESTs could be influenced by community racial distribution (% Black), but environmental constraints and events might shift implementation patterns.     

A socio-ecological perspective of urban green networks: the Stockholm case

Landscape fragmentation threatens habitats, biodiversity and other ecosystem services. In tackling this threat, the dynamic processes of social-ecological systems should be recognised and understood. Although network analysis based on graph theory has been recognised as an efficient way of spatially understanding landscape or habitat connectivity, only few studies have offered specific approaches or suggestions for integrating detailed social-ecological values into geographical distributions. As a contribution to bridging this gap, this paper introduces a social-ecological network model for the issue of landscape or habitat fragmentation applied to the case of Stockholm, Sweden. Graph theory was used in combination with sociotope and biotope maps for simple visualisation of network situations in two-dimensional maps. The European crested tit (Lophophanes cristatus), European common toad (Bufo bufo) and human beings were selected as indicator species, based on a landscape ecology analysis in Stockholm Municipality in 2009. Slope, land use and human disturbance maps were assessed in order to decide cost values of travelling from node to node. Lease-cost-path accumulation was used to create ideal reference maps of green networks. Three separate maps were then developed for suggesting efficient routes for three indicators in city scale that mainly connect from the Royal National City Park to the other parts of the city. The model in Hjorthagen neighbourhood to highlight two practical paths that link this fragmented community to its neighbouring park areas. Findings make it possible to address two scales of network improvement strategies, namely first for the city-scale green network that connects geographical habitats (nodes) and the regional green wedges of the city, and the second that of neighbourhood links between habitats in detailed layers of green networks. Strategic improvement potentials are presented based on ideal reference maps of green networks correspondingly.     

Who is leading the campaign charts? Comparing individual popularity on old and new media

Attention in the mass media is seen as crucial for electoral success. However, most ordinary candidates hardly get any attention in the news. With social media outlets becoming ever more popular, the question is whether the overall asymmetry in attention for candidates still holds today. Do candidates who dominate the traditional media during the campaign also dominate the social media? Or can candidates make up for a lack of mass media coverage by attracting attention on these new media platforms? This paper aims to answer these questions by pairing Twitter activity and Twitter popularity with newspaper attention for a large number of individual candidates in the 2014 Belgian election campaign. We expand the normalization versus equalization debate by not only looking at how much a new medium is used, but also at its success in terms of popularity and audience reach. Our findings show that the two platforms are indeed related, mainly because a small political elite dominates both old and new media. Twitter popularity and Twitter activity (albeit to a lesser extent) are higher among powerful politicians. We elaborate on why these findings are so much in line with the normalization hypothesis.     

Functional analysis of high-content high-throughput imaging data

High-content automated imaging platforms allow the multiplexing of several targets simultaneously to generate multi-parametric single-cell data sets over extended periods of time. Typically, standard simple measures such as mean value of all cells at every time point are calculated to summarize the temporal process, resulting in loss of time dynamics of the single cells. Multiple experiments are performed but observation time points are not necessarily identical, leading to difficulties when integrating summary measures from different experiments. We used functional data analysis to analyze continuous curve data, where the temporal process of a response variable for each single cell can be described using a smooth curve. This allows analyses to be performed on continuous functions, rather than on original discrete data points. Functional regression models were applied to determine common temporal characteristics of a set of single cell curves and random effects were employed in the models to explain variation between experiments. The aim of the multiplexing approach is to simultaneously analyze the effect of a large number of compounds in comparison to control to discriminate between their mode of action. Functional principal component analysis based on T-statistic curves for pairwise comparison to control was used to study time-dependent compound effects.     

Psychodynamic Couple Therapy: A Practical Synthesis

This essay reviews the most significant contributions of psychodynamic thought to the field of couple therapy. It distills the work of numerous clinicians and researchers who, though writing from diverse perspectives, share fundamental assumptions and concerns. Rather than emphasizing differences between schools of thought, this paper mines their best contributions in a discussion of five central therapeutic targets: underlying issues, divergent subjective experiences, transferences, projective identification, and acceptance. Two detailed cases illustrate the benefits and techniques for targeting these five therapeutic domains. Video Abstract is found in the online version of the article .     

Of bodies captured: the visual representation of the Paarl march and Poqo in apartheid South Africa

This article examines the visual representation of the violent march on the Western Cape town of Paarl in November 1962, and the place of photographs as employed by the media, a state-appointed commission of inquiry, and a series of judicial trials in the making of this event and its subjects. It is particularly concerned with a file of photographs of men accused of participating in the march, as a means to potentially enabling more complex and nuanced readings of the uprising than those provided by the textual archive surrounding the event. It considers the ways in which these photographs were used and why, while seemingly meant to give a face to a united Poqo organisation they never take on an altogether-public life. Clearly photographic occasions which were not as rigidly controlled as one would expect from police photographs, these photographs reference a multiplicity of genres. Yet at the same time, as the products of police surveillance, they remain deeply complicit in discourses of power and subjectification.     

Declining inter-industry wage dispersion in the US

Industrial effects have long been significant factors in wage inequality. Previous research indicates that wage differentials across industries were increasing through the mid 1980s. Using more recent data, however, we find that the level of inter-industry wage dispersion declined by 36% from 1986 to 2002 despite the continued trend towards increasing inequality in the labor force. This decline in inter-industry wage dispersion is evident across gender and educational groups. Using multilevel growth curve models, our multivariate results indicate that the decline is only weakly related to industrial changes in education, occupation or even productivity despite the fact that the latter variable had been a critical factor in the prior period. Indicators of globalization and downsizing also do not appear to explain this decline. For the more recent period, the most important factors associated with the narrowing of inter-industry wage dispersion are reduced unionization rates and the higher proportion of casual workers. We interpret these results as suggesting that firms may now be less economically obliged to pass on a portion of their rents to broad groups of workers and may instead be engaged in more idiosyncratic processes of negotiation with individual workers based on micro-level sources of bargaining power.     

Bullying and Victimization Among Young Elementary School Children: The Role of Child Ethnicity and Ethnic School Composition

School-aged children with an ethnic minority background are relatively often involved in bullying and victimization, but the role of ethnic composition of schools in this context remains unclear. This study examined the relation between ethnic minority background, ethnic school composition, and bullying behaviour around primary school entry in the Netherlands. The study was based on a 2008/2009 school survey in Rotterdam, a Dutch city where about 50 % of children have a non-Dutch background. For 8523 children, teacher reports of bullying behaviour at age 5–6 years were available. Children with a non-Dutch background had higher odds of being a victim (adjusted OR 1.41, 95 % CI 1.11, 1.80), bully (OR 1.38, 95 % CI 1.20, 1.58) or bully-victim (OR 1.38, 95 % CI 1.19, 1.62) than children of Dutch national origin. Ethnic diversity in schools increased children’s risk of bullying behaviour (e.g. OR_victim per 0.1 increase in 0–1 diversity range = 1.06, 95 % CI 1.00, 1.13), with children of both Dutch and non-Dutch national origin relatively more often involved in bullying in ethnically diverse schools. The proportion of same-ethnic peers in school reduced the risk of bullying among children of Dutch national origin (e.g. OR_victim per 10 % more same-ethnic children = 0.90, 95 % CI 0.83, 0.98), but not among non-Dutch children. In conclusion, ethnic minority background and ethnic diversity within schools are risk factors for bullying among 5–6 year olds. Plausibly, reductions in absolute numbers of bullying events may be obtained with tailor-made interventions in ethnically diverse schools. Such interventions should preferably be offered early in the school curriculum.     

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model. For a long time, however, likelihood-based estimation was only feasible for ERG models assuming dyad independence. For more realistic and complex models inference has been based on the pseudo-likelihood. Recent advances in computational methods have made likelihood-based inference practical, and comparison of the different estimators possible.