War's Long Shadow: Masculinity, Medicine, and the Gendered Politics of Trauma, 1914–1939
Bibliographic record
Abstract
War is an inherently traumatizing experience, and during the First World War more than 15,000 Canadian soldiers were diagnosed with some form of war-related psychological wounds. Many more went unrecognized. Yet the very act of seeking an escape from the battlefield or applying for a postwar pension for psychological traumas transgressed masculine norms that required men to be aggressive, self-reliant, and un-emotional. Using newly available archival records, contemporary medical periodicals, doctors' notes, and patient interview transcripts, this paper examines two crises that arose from this conflict between idealized masculinity and the emotional reality of war trauma. The first came on the battlefield in 1916 when, in some cases, almost half the soldiers evacuated from the front were said to be suffering from emotional breakdowns. The second came later, during the Great Depression, when a significant number of veterans began to seek compensation for their psychological injuries. In both crises, doctors working in the service of the state constructed trauma as evidence of deviance, in order to parry a larger challenge to masculine ideals. In creating this link between war trauma and deviance, they reinforced a residual conception of welfare that used tests of morals and means to determine who was deserving or undeserving of state assistance. At a time when the Canadian welfare state was being transformed in response to the needs of veterans and their families, doctors' denial that "real men" could legitimately exhibit psychosomatic symptoms in combat meant that thousands of legitimately traumatized veterans were left uncompensated by the state and were constructed as inferior, feminized men.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.021 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".