The Indigenous Casualties of War: Disability, Death, and the Racialized Politics of Pensions, 1914–39
Bibliographic record
Abstract
The First World War inflicted suffering upon hundreds of thousands of Canadian families between 1914 and 1918. In response, the state modernized its pension system to partially alleviate the postwar suffering of these families, reflecting the changing role of government in the lives of Canadians. To receive a pension after the war, Canadian veterans and dependants had to prove their postwar suffering arose directly from the battlefield, yet not all who qualified were accorded the same treatment. Unlike their non-Indigenous counterparts, external administrators were appointed to oversee the expenditure of pensions given to Indigenous veterans and dependants to ensure they were spent responsibly. Disabled Indigenous veterans and dependants recognized this as a profoundly discriminatory system – reducing them to their “Indian” identity – and drew from the nineteenth-century language of imperial nationalism and patriotism to demand equitable compensation and treatment from the state. Understanding the experiences of death and disability as intimately as the racist discrimination they faced, they envisioned their place as equals within the larger community of Canadian war casualties even though settlers and the state refused to recognize them as such.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".