Diana L. Di Stefano. Encounters in Avalanche Country: A History of Survival in the Mountain West, 1820–1920.
Bibliographic record
Abstract
For Diana L. Di Stefano, avalanches in the Mountain West were, during a hundred critically formative years there, not only frequent and voluminously dangerous descents (in accord with the word's etymology) of snow, ice, rock, earth, timber, and other debris on mountainsides, but also nexuses where significant historical forces—of regional identity, community-building, labor problems, litigation regarding acts of God, and more—encountered one another. Those downslides born of snowpack instabilities occurred as either loose-snow or slab avalanches, the latter usually the more massive of the two, more difficult to predict, and able to move at up to two hundred miles per hour. Both were formidable agents of large-scale destruction—of almost everything and everybody in their broad paths—in “Avalanche Country, places where steep slopes and snow converge with deadly potential” (p. 3). As Di Stefano argues emphatically, the people who contended with avalanches in the course of those hundred years, from Alaska and Canada to California and Colorado, were not the hell-bent-for-leather loners of the cinematic West but individuals—initially fur trappers and traders, then miners, mailmen, itinerant preachers, doctors, railway workers, and all manner of intrepid settlers—who learned by dint of menacing necessity to band together to develop the communal knowledge and share the skills and strategies that helped them as they strove to avoid sudden, violent, and suffocating burial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".