“Cleansing the Conscience of the People”: Reading Head Tax Redress in Multicultural Canada
Bibliographic record
Abstract
Résumé Cet article analyse les efforts déployés par des Canadiens d'origine chinoise pour obtenir compensation pour la taxe ( head tax )qm leur fut imposée, en explorant les discours social et politique entourant ce débat ainsi que le cas judiciaire, Mack et al. v. The Attorney General of Canada . Même si cette cause n'a jamais été décidée par les cours, sauf pour déterminer si des demandes de réparation avaient un fondement en droit canadien, le raisonnement judiciaire accompagnant les contestations de l'État et du public révèle les voies complexes de mythologies nationales canadiennes par lesquelles ces requêtes peuvent être influencées. L'argument central est que les cours, les politiciens et le public ont lu la campagne pour obtenir réparation des Canadiens d'origine chinoise à travers deux mythes nationalo-raciaux qui nourrissent les discours canadiens sur le multiculturalisme. L'auteur montre comment ces deux mythes – d'une part, celui de l'immigration comme ‘choix’ et, d'autre part, que les Canadiens d'origine chinoise seraient une ‘minorité modèle’ –ont influencé et façonné les réponses judiciaire, politique et sociale à la demande de compensation et ainsi diminué leur quête d'obtenir justice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.042 | 0.023 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".