Bibliographic record
Abstract
The Halifax Explosion of 1917 is a defining event in the Canadian consciousness, yet it has never been the subject of a sustained analytical history. Astonishingly, until now no one has consulted the large federal government archives that contain first-hand accounts of the disaster and the response of national authorities. Canada's recently established navy was at the epicentre of the crisis. Armstrong reveals the navy's compelling, and little-known, story by carefully retracing the events preceding the disaster and the role of the military in its aftermath. He catches the pulse of disaster response in official Ottawa and provides a compelling analysis of the legal manoeuvres, rhetoric, blunders, public controversy, and crisis management that ensued. His disturbing conclusion is that federal officials knew of potential dangers in the harbour before the explosion, took no corrective action, and kept the information from the public. As a result, a Halifax naval officer was made a scapegoat and the navy received lasting, and mostly undeserved, vilification. This is a provocative read not only for military and naval devotees but for anyone who wants to understand one of the events that shaped Canada in the twentieth century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".