Legislative Audit, at the Frontiers of Power and Politics
Bibliographic record
Abstract
En etudiant le mandat de Sheila Fraser comme Verificatrice generale (VG) du Canada de 2001 a 2011, cet article analyse la facon dont l’exercice de son pouvoir a permis de briser la structure de complicite qui tend generalement a lier l’action des Auditeurs legislatifs aux interets du champ politique. Notre etude s’articule en particulier autour du scandale du programme des commandites devoile par la VG en 2004 et des evenements qui ont suivi. Nos resultats mettent en evidence l’exercice d’un pouvoir multidimensionnel impliquant : 1) La mobilisation des armes reglementaires et legislatives permettant de provoquer des conflits ouverts avec le champ politique; 2) La defense du territoire reglementaire du VG et une pratique des missions d’audit de performance echappant au cadre restrictif d’une approche purement « technicienne »; 3) La production d’un discours installant dans l’imaginaire collectif une representation de l’action du VG comme un « justicier » independant des jeux politiques et au service de la population. Notre etude contribue ainsi a la litterature sur l’audit legislatif en mettant en evidence la complexite de la dynamique de pouvoir exerce par le Verificateur general et la porosite des frontieres des territoires reglementaires et politiques.
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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 | 0.011 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".