Megan J. Davies and Geoffrey Hudson (eds), <i>An Accidental History of Canada</i>
Bibliographic record
Abstract
This volume is a welcome contribution to the study of the accident from the 1630s to the 1980s. Drawing on previous accident studies, the editors organised a dozen Canadian case studies into sections defined as ‘Equity’, ‘Precaution’ and ‘Narratives’, but could have assembled them in other ways, including the state, workplace, childhood and even transport, a dominant cause of accidents across time and place. Simultaneously, it seeks to explore what is unique in the context of Canada, and here individual chapters invoke themes like margins, extremes and settler colonialism. The volume commences with a national disaster involving a supply vessel that exploded in Halifax harbour in 1917, instantly killing 1,600 people. The narrative quickly shifts to more ‘personal’ accidents, which claimed fewer lives, but were catastrophic in their own ways and shaped trauma narratives, if on smaller scales. Responsibility for accidents is addressed in the context of ‘individual freedom’ (p.8), but also federal and, in the Canadian context, provincial responses to such risks and injuries. Although existing literature is mentioned only briefly, the editors and authors discuss the construction of accident narratives and shared meaning in novel ways. This is immediately underlined by a study describing an accidental fire in 1903 that destroyed the efforts of Finnish immigrants to build a socialist utopia on the north end of Vancouver Island. At a time of increasing Finnish migration to Canada, fires and their destructive power dominated newspapers that catered to this community, often offering opportunities to attribute blame to ‘greedy’ bosses (39). Samira Saramo’s chapter explores how one isolated socialist community grieved, mourned and made sense of a fire that occurred outside the capitalist society they sought to escape. In short, it defied explanation and, consequently, was forgotten.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".