Bibliographic record
Abstract
Every province and territory in Canada has an independent ethics commissioner, along with ethics rules, and so too does the House of Commons, the Senate, and cabinet. The ethics regime for the House of Commons and the cabinet, however, appears to be the least successful of these ethics regimes in preventing breach of the rules. This article identifies the major weaknesses of the federal ethics regime. While in most other jurisdictions the ethics commissioner meets annually with all legislators to explain the rules, the extensive mandate of the federal ethics commissioner makes fulfilling the primary function – prevention through education – challenging. Face-to-face meetings between the ethics commissioner and members of the House of Commons and cabinet rarely occur. The author reviews inquiries made by the two House of Commons commissioners since 2004, and argues that many of the inquiries would have been unnecessary if face-to-face meetings had been held.
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 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 | 0.060 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.055 | 0.026 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.022 | 0.033 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".