Bill 34: The Safer Roads Act (Drivers and Vehicles and Highway Traffic Act Amended)
Bibliographic record
Abstract
ill 34 -The Safer Roads Act 1 was first introduced to the Manitoba Legislature on June 4, 2015 during the fourth session of the fortieth Legislature, 2 and subsequently received Royal Assent on November 5, 2015.3 The bill amended both The Drivers and Vehicles Act, 4 and The Highway Traffic Act, 5 with the overall objective to keep dangerous drivers off the road by targeting chronic bad drivers, as well as distracted and impaired driving offenders through implementation of immediate driver improvement actions, including license suspensions.6 It was stated by the Minister of Justice and Attorney General, the Honourable Gord Mackintosh (Mr. Mackintosh) that "the introduction of The Safer Roads Act sends a strong message that dangerous and illegal driving behaviours, such * J.D. (2017).
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.020 | 0.012 |
| Insufficient payload (model declined to judge) | 0.022 | 0.014 |
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".