The Case of Omar Khadr and the Fragilities of Canadian Citizenship: Le cas d’Omar Khadr et le modèle de citoyenneté canadienne à deux niveaux
Bibliographic record
Abstract
Reprinted from Vol. 4 (2019). Original Article: https://journals.library.ualberta.ca/psur/index.php/psur/article/view/102 English This paper focuses on Omar Khadr, a Muslim and Canadian citizen who was captured by American soldiers in a bombed-out Afghan compound in 2002. Khadr spent a decade of his life detained, often in solitary confinement, in Guantanamo Bay—a place infamous for allegations of torture. In 2012, Khadr pled guilty before an American military tribunal for throwing a grenade that fatally wounded an American soldier which he later recanted. This paper is a case study of how Khadr's story shows certain vulnerabilities to Canadian citizenship. More specifically, I will argue that Khadr's experience reinforces the notion that Canada does not always succeed at protecting its citizens and that formal citizenship alone does not guarantee one’s Charter rights. Francais Ce document se concentre sur le cas d’Omar Khadr, un citoyen canadien musulman ne a Toronto qui a ete capture par les forces armees americaines dans un complexe bombarde en Afghanistan en 2002. Khadr a passe une decennie de sa vie en detention, souvent isole, a Guantanamo Bay, pretant a controverse pour des allegations de torture contre ses detenus (citer). En 2012, Khadr a plaide coupable devant un tribunal militaire pour avoir lance une grenade qui a blesse mortellement un soldat americain — une reponse a l’accusation qu’il a ensuite retractee. Quant a la compensation de 10 millions de dollars et aux excuses du gouvernement liberal a Khadr, les Canadiens restent divises. En utilisant le cas d’Omar Khadr, je soutiendrai que le statut de citoyen canadien n’est pas une garantie absolue pour proteger les gens contre les abus, la depossession, la stigmatisation, les prejuges et la racialisation. De plus, je suggere que le Canada souscrit a une double norme lorsqu’il s’agit de proteger ses citoyens, comme en temoigne sa complicite dans le cas de Khadr, ainsi que son obstruction deliberee a son rapatriement. Plus important encore, j’ai l’intention de demontrer que la racialisation et les prejuges sont les principales raisons pour lesquelles Khadr a ete prive des protections et des droits qui auraient du lui etre garantis, etant donne sa citoyennete canadienne. Note: The translated title and abstract are based from the Vol. 4 (2019) article.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.061 | 0.025 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".