Catalog of Canadian Fitness Screening Protocols for Public Safety Occupations That Qualify as a Bona Fide Occupational Requirement
Bibliographic record
Abstract
Gumieniak, RJ, Jamnik, VK, and Gledhill, N. Catalog of Canadian fitness screening protocols for public safety occupations that qualify as a bona fide occupational requirement. J Strength Cond Res 27(4): 1168–1173, 2013—The purpose of this paper was to provide succinct descriptions of prominent job-specific physical fitness protocols (JSPFPs) that were constructed to satisfy the legal obligations to qualify as a bona fide occupational requirement for physically demanding public safety occupations. The intent of a JSPFP is to determine whether an applicant or incumbent possesses the necessary physical capabilities to safely and efficiently perform the critical on-the-job tasks encountered in a physically demanding occupation. The JSPFP information summarized in this report is accessible in full detail in the public domain. Therefore, prospective JSPFP participants and fitness professionals who require the information to train participants can fully inform themselves about the specific protocol requirements and associated fitness training implications.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.077 | 0.028 |
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".