The transition to safety management systems (SMS) in aviation : is Canada deregulating flight safety?
Bibliographic record
Abstract
In 2013, the International Civil Aviation Organization (ICAO) adopted Annex 19 to the Chicago Convention to implement Safety Management Systems (SMS) for airlines around the world.While most ICAO Member States worldwide are still in the early stages of introducing SMS, Canada became the first and only ICAO country in 2008 to fully implement SMS for all Canadian-registered airlines.This article will highlight the documented shortcomings of SMS in Canada during the implementation of the first ever SMS framework in civil aviation.While air carriers struggled to understand and introduce SMS into their operations, this article will illustrate how Transport Canada (TC) did not have the knowledge or the necessary resources to properly guide airline operators during this transition, how SMS was improperly tailored for smaller air carriers, and how the Canadian government canceled safety inspections around the country, leaving many air carriers partially unregulated.This article will argue that TC has effectively deregulated flight safety in certain areas of its aviation industry under SMS.Drawing on recent safety statistics and accident investigation reports, this article will illustrate how TC's inadequate safety oversight during the adoption of SMS resulted in several accidents, putting the traveling public at risk.To support these findings, * René David-Cooper graduated with a Master of Laws (LL.M.) at the Institute of Air and Space Law at
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".