15 YEARS OF AVALANCHE SAFETY IN QUEBEC (CANADA)
Bibliographic record
Abstract
ABSTRACT: Historically overlooked in Quebec, snow avalanches nonetheless resulted in 73 fatalities across the province between 1825 and the present day. Beginning 15 years ago, the development of winter tourism in the Chic-Chocs Mountains revealed the need for avalanche safety programs. Therefore, the Centre d’avalanche de la Haute-Gaspésie was created in 1999 to promote backcountry safety among Quebec’s skiers, who are known to travel far and wide in pursuit of their sport. The first service to emerge was a forecasting program that issued a snow bulletin once a week to inform backcountry users of condi-tions in the mountains. Today, a bilingual avalanche bulletin, issued every two days from December 1st to April 30th, highlights the danger rating and avalanche problems. In the early 2000s, the Canadian Ava-lanche Association (CAA) came to Quebec to help develop expertise by offering avalanche, weather and search and rescue professional training. To date, more than 150 students have taken CAA courses in the province. Public awareness activities have also successfully informed and educated youth and winter enthusiasts through public conferences, Avalanche Skills Training courses, workshops and Avalanche Awareness Days held for the last 10 years in the Chic-Chocs. All these programs have the common goal to improve avalanche safety, reduce risk of accidents and thus save lives. Unique in Eastern Cana-da, this not-for-profit organization is now working toward a provincial recognition and is in the process of changing its name to Quebec Avalanche Centre or Avalanche Quebec.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".