Women's Human Rights and Canadian Tax Policy: From CEDAW to the Beijing Platform and Beyond
Bibliographic record
Abstract
Les gouvernements canadiens ayant systematiquement coupe les impots dans les annees ‘90 alors que le Canada a occupe pendant plusieurs annees le premier rang dans l’indice du developpement humain aux Nations Unies et dans l’egalite des sexes, en 2001, il etait descendu au 23e rang, encore plus bas dans l’indice genree du Forum de l’economie mondiale. Ce texte accuse les coupes dans les impots de discrimination envers les femmes sous quatre chefs: d’abord en justifiant les austerites budgetaires ; en privatisant les revenus inegalement entre les sexes; en beneficiant hors de proportion le capital prive, les investisseurs et les hommes d’affaires souvent plutot que des femmes; finalement en stereotypant le role de l’homme comme gagne-pain au detriment de la femme aidante ou occupee dans les tâches peu payees. L’auteure analyse ces coupes budgetaires depuis 1995 et termine avec des recommandations qui seront implantees dans le CEDEF et dans la Plateforme d’action de Beijing. D’autres recommandations visent toutes les politiques de taxation et les programmes de depenses qui respecteront l’egalite des femmes et corrigeront toute discrimination presente dans la taxation canadienne.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".