A Systematic Review of Military to Civilian Transition: The Role of Gender
Bibliographic record
Abstract
Abstract Background The military-to-civilian transition can be a challenging period for many service members; however, recent research suggests that female ex-service personnel (veterans) confront additional complexities during reintegration into civilian life. This systematic review aimed to identify and synthesise findings across qualitative studies exploring the impact of gender on this transition process. Methods Peer-reviewed literature was drawn from a multi-database search, limited to qualitative studies. The studies included either female veterans or both male and female veterans aged 18 years or older who had previously served in the Armed Forces within the Five Eyes (FVEY) countries (Australia, Canada, New Zealand, the United Kingdom, and the United States). We used a Framework Analysis approach to guide the synthesis of the qualitative data. An assessment of study quality was conducted using the Joanna Briggs Institute (JBI) Qualitative Critical Appraisal Checklist for Qualitative Studies. The study protocol is registered with the Open Science Framework (osf.io/5stuj). Results In total, 10,113 articles were screened after the removal of duplicates, 161 underwent full-text review, with 19 meeting the eligibility criteria. The review identified eleven themes split across individual’s experience whilst serving and after transitioning out of the military service. Both male and female veterans discussed a period of acculturation when they joined service and adapted to military norms, culture and identity. Female veterans faced additional challenges at this stage centred on the conflict between feminine norms and the military masculine ideal. Upon leaving service both male and female veterans experienced a loss of military identity and purpose, and dissonance with civilian norms illustrating a military-civilian divide. For female veterans, adjustments and adaptations learned in the military clashed with civilian feminine norms and stereotypically male veteran culture. Female veterans also struggled with the legacies of gender inequality, discrimination, and sexual assault which affected their development of a female veteran identity and affected the provision of services designed to meet their needs as a female. Despite these challenges, female veterans’ expressed pride in their service and accomplishments. Conclusions Any effort to improve the military-to-civilian transition should take account of the legacy of gender discrimination, especially within the military service, and the potential mismatch between historical civilian female norms and the more traditionally masculine norms of military life. Disclosures This project was supported by a grant from the Forces in Mind Trust (FiMT) 2202. Full ethical clearance was granted by the Health Faculties Research Ethics Subcommittee, King’s College London. Project Reference: HR/DP-22/23-33303.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".