Gender in Veteran reintegration and transition: a scoping review
Bibliographic record
Abstract
Introduction: This article presents the results of a scoping review of Canadian and international literature on gender and Veteran reintegration and transition. Methods: The scoping review yielded 178 articles, which were organized thematically according to issues impacting Veterans' transition to civilian life and by their approach to gender. Results: There has been an upswing in gender research on Veterans, with 100 of the 178 articles published between 2000 and 2015. Most of the research articles, largely quantitative studies, are related to health issues ( n=108), discussing mental and physical health outcomes and health services use. There is much less gender-related research being conducted on socio-economic themes ( n=25) of Veterans' homelessness, employment, and education. Military sexual trauma (MST) represents the second most common topic ( n=45) researched in the reviewed literature, and appeared primarily in the context of health research and, to a lesser extent, in relation to socio-economic issues. Discussion: Lack of clarity on the use of the term “Veteran” and lack of explicit engagement with military-to-civilian transition in the reviewed literature pose challenges. Furthermore, the lack of qualitative research, social sciences research, and Canadian research represent major gaps in the literature. We recommend that the impact of military and civilian gender norms and gendered power dynamics be considered in relation to female, male, and LGBTQ Veterans across transition stages and across health and socio-economic dimensions in future research and programming.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".