COLLECTING AND PRESERVING THE HISTORY OF SNOW AVALANCHE ACTIVITY, RESEARCH AND SAFETY IN CANADA
Bibliographic record
Abstract
4 Avalanche Technician and Historic Researcher, Revelstoke, BC, Canada ABSTRACT: Collecting and preserving the objects and records of avalanche activity, research and safety provides valuable historic resources to avalanche professionals, the public and researchers in a variety of disciplines. Not only do these collections give insight into the nature of avalanches, they help focus and substantiate safety and research programmes. As a public education project to present a nationwide overview of avalanche science and safety for the Virtual Museum of Canada, we addressed the question of where and how avalanche archival resources are acquired, stored and indexed in Canada. Through discussions and interviews, site visits to museums and archives and internet-based collection searches, we identified existing archival resources and added new objects and metadata to these collections. We found well-archived avalanche incident records since 1782 including 884 avalanche-related deaths and we were able to map most of these fatalities. We found few resources documenting the experience of Aboriginal peoples with avalanches or three-dimensional artifacts from any time period (e.g., contempo- rary snow measurement tools). For the most part, publicly accessible archival resources were poorly in- dexed and most often discovered within collections catalogued to other subject areas such as transportation and mining. Archival resources related to the present-day transportation and recreation industries were poorly represented in formal archives and museums and often lacked detailed metadata. Avalanche safety and snow research professionals working in cooperation with museums, archivists and historians could help to illuminate significant chapters of Canadian history and provide information of on- going value to many sectors of the economy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.021 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".