Naval officer selection in Canada : an evaluation of the Maritime Officer Selection Test (MOST)
Bibliographic record
Abstract
Two studies evaluating the Maritime Officer Selection Test (MOST) were conducted. Study 1 ( N = 744) examined the psychometric properties of the individual items and their factorial structure. Study 2 ( N = 224) assessed convergent validity and sought to determine whether using the MOST for the selection of future naval officers might discriminate against women, thereby precluding them from pursuing a career within the Canadian Navy. The results of the first study indicate that most examinees do not have enough time to complete the test, which invalidates previous evaluations of its internal consistency. Additionally, the two studies suggest that the MOST does not measure what it was intended to assess (i.e., memory, selective attention, and decision-making), but that it does nonetheless evaluate other ability constructs required for naval officer training performance (i.e., spatial scanning and general reasoning). With regards to adverse effect, the absence of differential item functioning and similarities in success rates across genders indicate that using the MOST does not preclude women from pursuing a career within the Canadian Navy.
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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 | 0.014 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".