Examining the efficacy of inoculation and value‐affirmation interventions in improving precandidate reactions among prospective military recruits
Bibliographic record
Abstract
Abstract This study engaged 4848 first‐time, English‐speaking prospective Canadian Armed Forces applicants to evaluate pre‐application interventions' efficacy on the Practice Canadian Forces Aptitude Test (PCFAT). Using a five‐level between‐subjects design, participants were randomly assigned to one of the following intervention conditions: inoculation message, value‐affirmation message, a combination of both, placebo writing intervention, or a no‐intervention control group. The interventions were anchored in inoculation theory and value‐affirmation theory and aimed to reduce math anxiety and close the gender gap in test performance. Contrary to expectations, the interventions did not significantly reduce math anxiety or improve problem‐solving performance. Consistent with the literature, a negative relationship was found between levels of math anxiety and problem‐solving scores, and men outscored women in problem‐solving across all conditions. Despite these outcomes, the study lays a foundation for future research on enhancing pre‐applicant experiences in an increasingly competitive labor market. Implications and future directions are discussed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".