State, Service, and Survival: Canada’s Great War Disabled, 1914-44
Bibliographic record
Abstract
The following dissertation examines the little-known history of Canada’s Great War disabled. During the Great War Canada mobilized 620,000 soldiers, most of them volunteers. Nearly 120,000 would one day receive compensation for a disability incurred on, or aggravated by military service. Thousands more suffered from related injuries, diseases, or traumas but lacked the documentary evidence necessary to garner material support from the state. The core objective of this dissertation is to explore how policy-makers responded to these challenges, and how their efforts shaped the daily experiences of veterans from all walks of life. By fusing an analysis of policy with a social history of disability, this study uncovers the multiple paths disabled veterans embarked upon during their civil re-establishment. Few followed unfirom trajectories. The affects of disability on a veteran’s wellbeing varied widely based on numerous factors including pre-war social standing, support networks, material resources, age, and overall health. While most studies of disability and the Great War have focued on the cultural, medical, or political impact of disability, few adequately explain how both government policy and extraneous forces affected the lives of disabled veterans. Utilizing a wealth of statistical data and a large sample group of case files, “State, Service, and Survival: Canada’s Great War Disabled, 1914-44” is the first Canadian study to address this gap in our collective understanding of the war’s legacy.
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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 | 0.003 | 0.008 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".