Cultural Adaptation in Five Eyes Veterans Transitioning to Civilian Life: A Scoping Review Protocol
Bibliographic record
Abstract
This project hosts materials related to a Joanna Briggs Institute (JBI)-aligned scoping review protocol examining cultural adaptation among post-9/11 veterans from the Five Eyes nations (United States, United Kingdom, Canada, Australia, and New Zealand) transitioning from military to civilian life. The review maps how cultural adaptation and related constructs have been defined, measured, and theorized across the literature. It also identifies impacts, interventions, and evidence gaps to guide future research, practice, and policy supporting veteran reintegration. Affiliated Institutions: University of North Texas Health Science Center, College of Nursing The University of Texas at Tyler, College of Nursing and Health Sciences Funding and Institutional Support: The first author (R.S.) is a Jonas Scholar and has received financial support from Jonas Philanthropies to support his doctoral studies. Publication fees were supported by the Associate Dean of Undergraduate Nursing, College of Nursing, University of North Texas Health Science Center (UNTHSC). Funders had no role in the design, conduct, analysis, or preparation of this protocol.
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 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 | 0.153 | 0.137 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.057 | 0.013 |
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".