Balancing fidelity,contextualisation, and innovation: learning from an adaption of SASA! to prevent violence against women in the Dadaab refugee camp

ABSTRACT

This article focuses on SASA!, a community mobilisation approach that was developed in Uganda by Raising Voices, with the aim of preventing violence against women. SASA! proved effective in reducing intimate partner violence against women, and has since been used in over 25 countries worldwide. In this article, we draw on recent research into the International Refugee Committee’s implementation of SASA! in Dadaab, Kenya. In particular, we focus on how the refugee camp setting shapes the adaptation and delivery of the SASA! programme and explore the balance to be struck between fidelity to the SASA! methodology, and adaptations to make it suitable for use in this specific humanitarian context.     

Land,territory and commons: voices and visions from the struggles

ABSTRACT

All over the world, financial capitalism and extractivism are appropriating land as if it was nothing more than a commodity, a mere ‘factor’ of production that can be exploited to generate financial returns. Movements and activists are organizing, resisting, protecting and promoting life-giving visions against this continuous enclosure of living beings and paces: they use their bodies, laws, educational projects, histories and visions to regain control over territory as a political space, self-determine and create solidarities. In the act resistance, they are the target of moral, physical and legal violence. They and their ideas are criminalized, disciplined, punished and in some cases exterminated. In this contribution, activists from the Basque Country, Guatemala, Kenya and the Six Nations and a group of academics get together to learn from each other, support the ongoing search for common vocabularies and identify possible milestones of a coordinated and international strategy for a life-enhancing future.     

City dwelling wild bees: how communal gardens promote species richness

Urban areas consist of wide expanses of impervious surfaces which are known to negatively affect insect biodiversity in general, but green spaces within cities have the potential to provide necessary habitat and foraging resources. Although, communal gardens were primarily intended to provide fresh, regional food to denizens, these green islands also host a surprisingly high number of wild bee species.

The gardens were characterized based on structural elements such as flower frequency, the relative percentage of lawn, trees, shrubs, planted crops and infrastructure (e.g. seating possibilities or garden houses). Further, the effects of different landscape structures surrounding the gardens and distance to the city center were analyzed on the total wild bee species richness and functional traits. Focusing on these putative influencing factors, statistical analyses calculating random decision forests along with generalized linear mixed models were applied. With 113 observed wild bee species, communal gardens provide habitat for a quarter of all known species in Vienna. In conclusion, results revealed that only elements within the gardens had an effect on species richness, with flower frequency as the major positive driver. The examined communal gardens promote and conserve wild bees independent from the location within the city or garden size. Furthermore, these green patches are important sanctuaries, hosting rare and threatened species as well as remarkably special wild bee communities.

     

Predictors of Adolescent Participation in Organized Activities: A Five‐Year Longitudinal Study

This study examined (a) growth curves of youth participation in sports, performance and fine arts, and youth clubs throughout the high school years and (b) the associations between a series of predictors and the initial participation rates and growth over time. The predictors included individual, friend, and family factors. The moderating effect of youths' gender was also examined. Study participants were 272 youths (55% girls, M_age=12.4 years) and their parents. The predictors were assessed in Grade 6 and were based on reports by youths, parents, teachers, and classmates. Participation in organized activities was assessed annually from Grades 7 to 10. Altogether, the findings revealed that participation in sports, performance and fine arts, and youth clubs remains stable across the high school years. However, interindividual differences were found in the participation growth curves. This variation was predicted by individual, friend, and family factors, mostly with respect to sports activities.     

Gerontocracy in a comparative perspective: Explaining why political leaders are (almost always) older than their constituents

Gerontocracy, in its narrowest sense, refers to political systems ruled by elderly people, whether de jure or de facto. Although formal gerontocratic rules are progressively disappearing, contemporary political systems are still governed by individuals who are significantly older than the mean voter. This article reviews existing explanations for the prevalence of gerontocracy. To summarize main findings, gerontocracy cannot be explained by the leadership qualities of older rulers: aging leaders do not perform better in office and voters seem to be aware of it. Instead, existing research suggests that gerontocracy can be explained by strategic considerations. In autocracies, the selectorate tends to choose aging leaders in order to reduce their expected tenure length. In democracies, voters are more likely to select experienced candidates, which they expect to be more effective at advancing the interests of their constituency: this premium put on experience mechanically lengthens political careers and increases the age of the average politician. Finally, older voters, which participate more in politics, tend to prefer older politicians, because they (correctly) expect them to better defend their own interests.     

Relations between Theory of Mind and Indirect and Physical Aggression in Kindergarten: Evidence of the Moderating Role of Prosocial Behaviors

The present study examined the association between theory of mind and indirect versus physical aggression, as well as the potential moderating role of prosocial behavior in this context. Participants were 399 twins and singletons drawn from two longitudinal studies in Canada. At five years of age, children completed a theory of mind task and a receptive vocabulary task. A year later, teachers evaluated children's indirect and physical aggression and prosocial behavior. Indirect aggression was significantly and positively associated with theory of mind skills, but only in children with average or low levels of prosocial behavior. Physical aggression was negatively associated with prosocial behavior but not with theory of mind. Each analysis included gender, receptive vocabulary, and the respective other subtype of aggression as control variables. These results did not differ between girls and boys or between twins and singletons. Theoretical and clinical implications of these findings are discussed.     

Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain

The Monte Carlo (MC) simulation approach is traditionally used in food safety risk assessment to study quantitative microbial risk assessment (QMRA) models. When experimental data are available, performing Bayesian inference is a good alternative approach that allows backward calculation in a stochastic QMRA model to update the experts’ knowledge about the microbial dynamics of a given food‐borne pathogen. In this article, we propose a complex example where Bayesian inference is applied to a high‐dimensional second‐order QMRA model. The case study is a farm‐to‐fork QMRA model considering genetic diversity of Bacillus cereus in a cooked, pasteurized, and chilled courgette purée. Experimental data are Bacillus cereus concentrations measured in packages of courgette purées stored at different time‐temperature profiles after pasteurization. To perform a Bayesian inference, we first built an augmented Bayesian network by linking a second‐order QMRA model to the available contamination data. We then ran a Markov chain Monte Carlo (MCMC) algorithm to update all the unknown concentrations and unknown quantities of the augmented model. About 25% of the prior beliefs are strongly updated, leading to a reduction in uncertainty. Some updates interestingly question the QMRA model.