Bibliographic record
Abstract
In this article, I examine how the politics of representation following September 11, 2001 attacks on the US impact the experiences of Somali youth in educational spaces in North America. This research draws from a discourse analysis of representations of Somalis and Somalia in North American newspaper articles (n=82) between August and October 2011 and 51 interviews with Somali youth between the ages of 14 and 30. It also draws from ethnographic fieldwork for 16 months (July 2010−October 2011) in Kitchener-Waterloo and Toronto, Canada and Minneapolis-St. Paul, USA. This includes participant-observation at Somali youth events, organizations, centres, homework programs, mosques and after-school and weekend Islamic schools that provide spaces of learning for Somali youth outside of public/private schools. In this article, I argue that the representations of Somalis in the media as either perpetrators or victims of violence are gendered and have variously politicized Somali men and women within the current ‘War on Terror.’ As a result, Somali youth are targets of routine forms of structural violence, expressed in discrimination and marginalization as well as interpersonal forms of violence, including bullying. I examine how these forms of violence are both carried out and resisted in educational spaces and how they variously affect Somali youth’s experiences in school. The article shows how Somali community educational spaces provide spaces of belonging and a space to learn the skills needed to challenge representations of Somalis and Somalia in the media. Somali youths’ experiences of violence and within educational spaces reshape their identities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".