Making military and Veteran women (in)visible: The continuity of gendered experiences in military-to-civilian transition
Bibliographic record
Abstract
LAY SUMMARY This study explores how gender and sex shape the military-to-civilian transition (MCT) for women. Thirty-three Canadian women Veterans were interviewed about their military service and post-military life. MCT research often emphasizes discontinuities between military and civilian life, but women Veterans’ accounts highlight continuities in gendered experiences. Military women are expected to fit the male norm and masculine ideal of the military member during service, but they are rarely recognized as Veterans after service. Women experience invisibility as military members and Veterans and simultaneously hypervisibility as (ex)military women who do not fit military or civilian gender norms. Gendered expectations of women as spouses and mothers exert an undue burden on them as serving members and as Veterans undergoing MCT. Women encounter care and support systems set up on the normative assumption of the military and Veteran man supported by a female spouse. The study findings point to a needed redesign of military and Veteran systems to remove sex and gender biases and better respond to the sex- and gender-specific MCT needs of women.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".