Bibliographic record
Abstract
L'auteur analyse la transparence dont Revenu Québec fait preuve dans son mandat d'administrer les lois fiscales du Québec et la taxe fédérale sur les produits et services sur le territoire du Québec.Il le fait sous trois angles : transparence dans l'interprétation donnée par Revenu Québec aux textes législatifs, transparence dans sa manière de les appliquer et transparence dans la divulgation ponctuelle de sa performance et de ses résultats.This article examines the transparency displayed by Revenu Québec in administering Quebec tax laws and the federal goods and services tax on the Quebec territory.The transparency is analysed from three perspectives, first by considering the interpretation of tax laws by Revenu Québec, then by examining the manner in which they are applied, and finally by reviewing to what extent the performance of Revenu Québec and the results achieved are timely disclosed.L'Agence du revenu du Québec, mieux connue sous l'appellation « Revenu Québec », a été créée le 1 er avril 2011, pour appliquer les principales lois fiscales du Québec.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".