Validation of the Canadian Forces Aptitude Test using QL3 RMS clerk training criteria
Bibliographic record
Abstract
This study examines the Canadian Forces Aptitude Test (CFAT) as a measure of cognitive ability, along with military experience and education as predictors of training performance success on entry-level training for the Resource Services Management (RMS) clerk course. While validation evidence exists which suggests that cognitive ability (i.e., VSPS composite) predicts overall performance on the QL3 RMS clerk training, this study further demonstrated that using a measure of cognitive ability in isolation might not be the best method of selecting candidates for training. Specifically, because the CF uses experienced serving personnel to fill entry-level training positions, experience interacts with cognitive ability such that as experience increases cognitive ability becomes less important. Further, educational level was not only highly predictive for entry-level candidates (i.e., 1-3 years experience) but also significantly added to incremental validity beyond cognitive ability suggesting that it may represent a better method of selection for new recruits entering the CF.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".