Prospective Multifactorial Analysis of Canadian Forces Basic Training Attrition
Bibliographic record
Abstract
The aim of this prospective study was to identify key predictors of attrition from Canadian Forces basic training. Baseline health data from 5,169 Canadian Forces recruits (85.4% men) collected using the Recruit Health Questionnaire were linked with administrative data on basic training releases. A total of 8.0% of recruits from this sample was released from basic training. A wide range of factors falling within each of the following categories were examined as potential predictors of attrition: demographic characteristics, social environment, health status, lifestyle, and personality. Logistic regression analyses pointed to increased odds of attrition among noncommissioned member candidates, recruits with one or more dependents, as well as those with an annual household income of less than $20,000, poor/ fair self-rated health, medium/high severity of somatic symptoms, higher neuroticism, lower mastery, and higher agreeableness. Overall, results underscored the importance of good general health and resilient personality to basic training success.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".