Constitutions, regles et reglements de l'Assemblee legislative du Canada.
Bibliographic record
Abstract
Having, by Resolution of the Houseon the 5th March, been empowered to consider whether any and what improvements could be made in the Orders and Practice of The House, so as to facilitate the transaction of business, and the observance of order and decorum, and having received the assistance of the Honorable Gentlemen who were appointed to act as a Committee to aid me in this matter, I beg leave respectfully to submit to The House a new Code of Rules, as the result of our joint deliberations : " Our present Book of Rules and Standing Orders, as The House is aware, contains 97 Rules and 28 Orders, in all 125.Many of these have been added, from time to time, by direction of The House, but have not been suitably incorporated with the existing Rules.With the help and counsel of the Committee, I have carefully revised, consolidated and amended the language of the entire series, expunged such as were obsolete, and intro- duced others, embodying recent alterations in the Practice of The House.The actual changes I have recommended have been few in number, and of minor import, and have been intended either to conform our Rules with the recognized usage of the House, or to facilitate the transaction of Business by the introduction of some EXTRAIT DU RAPPORT
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 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".