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Record W4402310317 · doi:10.1522/revueot.v33n2.1802

Intégrité publique au Canada : description, critiques et observations des réformes proposées par le projet de loi C-290 à la Loi sur la protection des fonctionnaires divulgateurs d’actes répréhensibles

2024· article· fr· W4402310317 on OpenAlexaffvenueabout
Jeanne Simard, Jordan Mayer, France Aubin

Bibliographic record

VenueRevue Organisations & territoires · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversité LavalUniversité du Québec à Trois-RivièresUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

En 2007, la Loi sur la protection des fonctionnaires divulgateurs d’actes répréhensibles a été instaurée pour protéger tous les fonctionnaires fédéraux canadiens, sauf quelques exceptions. Cependant, cette loi est devenue rapidement obsolète et inefficace, notamment en ce qui concerne la confidentialité des lanceurs d’alerte et leur protection contre les représailles. Comparée aux lois internationales, elle est jugée insuffisante. Face à l'inaction du gouvernement, un député de l’opposition a proposé en juin 2022 le projet de loi C-290, visant à réformer la loi de 2007 et à modifier la Loi sur les conflits d’intérêts. Adopté à la Chambre des communes le 31 janvier 2024, ce projet devrait entrer en vigueur d'ici fin 2024. Cet article examine d’abord les dispositions de la loi de 2007, puis les critiques qu’elle a reçues, et enfin les améliorations proposées par le projet de loi, tout en soulignant les lacunes qui persistent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.862

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0210.015
Scholarly communication0.0140.003
Open science0.0030.005
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.046
GPT teacher head0.273
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

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