Bibliographic record
Abstract
This paper applies a broad definition of violence to the physically and economically vulnerable situation of Canadian military wives. Its reports some of the results of an institutional ethnography of Canadian military wives ' work which was carried out during the early 1990s, and which made some important discoveries about how the military's priorities and forms of organization structure the way the military treats wives, tries to control wives, and benefits from wives' unpaid work. The military's major priority, combat readiness, necessitates the control the military exercises over its members and the specific mechanism of military control known as combat unit bonding. Combat bonding is in turn characterized by cultural homogeneity and its corollaries of sexism, racism, derogation of, and violence against women. Nevertheless, the military extends a diluted form of combat bonding to military wives, in order to exert control over them and appropriate their unpaid labour, loyalty — and frequently, silence. Combat-related obsession with unit morale also often translates into the cover-up of problems, which is a consideration that adds to the isolation of the many survivors of woman abuse who are members of the military community. The greater public accountability of the Canadian military which may result from the Somalia Inquiry makes this an especially opportune time to study woman abuse and other forms of family violence in the Canadian military community.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".