Canada v. Asad Ansari: Avatars, Inexpertise, and Racial Bias in Canadian Anti-Terrorism Litigation
Notice bibliographique
Résumé
This essay examines the case of Asad Ansari, who was 25 years old at the time of his trial as part of the so-called Toronto 18. Through a close examination of certain aspects of his case, this essay will show that rather than Asad Ansari, what was on trial was an avatar of Ansari, which took shape through the explicitly inexpert and implicitly racially biased litigation of Islam itself. The very structure of the litigation collapsed Islam, the religion, into the defendant. The absurdity of this absent expertise is pregnant in the facially neutral, but substantively suspect, procedural structure of the litigation via the form of evidentiary motions and the use of leading questions on cross-examination. This procedural structure was substantially suspect in the case of Ansari because utterly inexpert testimonies and biased perspectives were permitted by the very structure of Canada’s adversarial system of justice. From the accused Ansari, to the government prosecutors, and even to the government paid confidential informants, no one was disinterested in the outcome of the trial. Yet none were duly certified by the court as impartial experts on Islam, jihad or the regional conflicts in Iraq, Syria or Afghanistan, despite all of them testifying about such matters as proxies for the defendant’s state of mind. Nor did the presiding judge Justice Fletcher Dawson—in the role of the paternal (if not patronizing) overseer of the jury—recognize the relevant parties were litigating matters outside their personal and institutional competency. The analysis below suggests that Ansari was found guilty not because he contravened anything that would fall within the anti-terrorism legislation. Rather, his guilt is premised upon the fact that he read, reviewed, and thought about ideas that the security state considers radical and even threatening. Because those ideas were embedded in propaganda from groups like al-Qaida, the Taliban, and Iraqi insurgencies, ultimately the person of Ansari was collapsed into these hard to find and harder to defeat groups.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».