Determinants of adjustment and well-being among Canadians posted to the United States
Bibliographic record
Abstract
Introduction: Out-of-country postings constitute an important aspect of military operations and frequently present unanticipated challenges and opportunities for individual service members and their families. However, research assessing the experience of Canadian Armed Forces (CAF) members who are posted outside Canada (OUTCAN) is scarce. The aim of this project was to 1) better understand the realities associated with OUTCAN postings to the United States and determine their impact on the well-being and adaptation of CAF members and their families and 2) establish an evidence-based approach to developing accessible, engaging material that could be incorporated into realistic previews to prepare military personnel and their families for international postings. Methods: CAF members and spouses posted to the United States (n = 231) participated through a focus group or interview, during which they described the challenges, benefits, and unanticipated aspects of their posting. Data were analyzed using open coding, an inductive approach to qualitative analysis. Results: Although participants described both challenges and opportunities associated with their respective postings, the challenges of an OUTCAN posting were regarded as having a more pronounced impact on adjustment and well-being and are therefore the focus of this article. Key themes included relocation, financial considerations, health care, isolation, children's education, spousal employment, cultural differences, bureaucracy, work demands and tempo, and environmental challenges. Discussion: These findings, and their impact on the well-being and adjustment of CAF personnel and dependants posted to the United States are described in detail, along with limitations of the study and directions for future research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".