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"Though interpersonal violence is widely studied, much less has been done to understand structural violence, the often-invisible patterns of inequality that reproduce social relations of exclusion and marginalization through ideologies, policies, stigmas, and discourses attendant to gender, race, class, and other markers of social identity. Structural violence normalizes experiences like poverty, ableism, sexual harassment, racism, and colonialism, and erases their social and political origins. The legal structures that provide impunity for those who exploit youth are also part of structural violence's machinery. Working with Indigenous, queer, immigrant and homeless youth across Canada, this five-year Youth-based Participatory Action Research project used art to explore the many ways that structural violence harms youth, destroying hope, optimism, a sense of belonging and a connection to civil society. However, recognizing that youth are not merely victims, Everyday Violence in the Lives of Youth also examines the various ways youth respond to and resist this violence to preserve their dignity, well-being and inclusion in society."--

AbstractThe prioritization of genes within a candidate genomic region is an important step in the identification of causal gene variants affecting complex traits. Surprisingly, there have been very few reports of bioinformatics tools to perform such prioritization. The purpose of this article is to investigate the performance of 3 positional candidate gene software tools available, PosMed, GeneSniffer and SUSPECTS. The comparison was made for 40, 20 and 10 Mb regions in the human genome centred around known susceptibility genes for the common diseases breast cancer, Crohn's disease, age-related macular degeneration and schizophrenia. The known susceptibility gene was not always ranked highly, or not ranked at all, by 1 or more of the software tools. There was a large variation between the 3 tools regarding which genes were prioritized, and their rank order. PosMed and GeneSniffer were most similar in their prioritization gene list, whereas SUSPECTS identified the same candidate genes only for the narrowest (10 Mb) regions. Combining 2 or all of the candidate gene finding tools was superior in terms of ranking positional candidates. It is possible to reduce the number of candidate genes from a starting set in a region of interest by combining a variety of candidate gene finding tools. Conversely, we recommend caution in relying solely on single positional candidate gene prioritization tools. Our results confirm the obvious, that is, that starting with a narrower positional region gives a higher likelihood that the true susceptibility gene is selected, and that it is ranked highly. A narrow confidence interval for the mapping of complex trait genes by linkage can be achieved by maximizing marker informativeness and by having large samples. Our results suggest that the best approach to classify a minimum set of candidate genes is to take those genes that are prioritized by multiple prioritization tools.