Testing a Resilience Model Among Canadian Forces Recruits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Evidence suggests that personal characteristics serve as resilience factors, and may protect military personnel against the development of psychological distress, even during stressful conditions. Structural equation modeling analyses were conducted on data from Canadian Forces candidates undertaking their basic training (N = 200) to test the fit of a model of resilience that is comprised of several individual characteristics, such as personality, hardiness, and coping. The most parsimonious model of resilience with the best fit to the data was identified. This model consisted of neuroticism, military hardiness, and problem-solving coping. The results of the study were consistent with previous research, showing that personality, military hardiness, and coping are important predictors of life satisfaction and health. The proposed resilience model offers a useful approach for the development of training programs to enhance readiness and recovery in the military context.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it