Establishing a physical fitness screening protocol for Correctional Officer applicants in accord with the Supreme Court of Canada's Meiorin Decision on bona fide occupational requirements
Bibliographic record
Abstract
Pre-employment physical abilities tests (PEPATs) have been utilized in physically demanding safety-related occupations for over three decades. In 1999, the Supreme Court of Canada's Meiorin Decision imposed definitive requirements for a PEPAT to qualify as a bona fide occupational requirement (BFOR). This led to the suspension of the existing PEPAT in Correctional Officer (CO) applicants. A National BFOR Consensus Forum established a template for the development, validation and evaluation of BFORs. The purpose of the present research was to develop a PEPAT for CO applicants to conform to the template of the BFOR Forum and comply with the Meiorin requirements. A physical demands analysis (PDA) involving 190 incumbent COs provided a rank-ordered list of the most important, most physically demanding and frequently occurring tasks encountered on the job by COs. A physiological characterization while these tasks were being performed by safe and efficient incumbent female COs, confirmed their high physical demands (VO 2 = 39.5 ± 4.3 ml·kg -1 ·min -1, HR = 177+11 bpm) and provided the criterion-based forces and aerobic fitness to control and restrain inmates (Wrist Hold = 71±14 kg, Arm Restraint/Retraction = 82±18 kg, Push/Pull =101±15 kg). The "Fitness Screening Protocol for Correctional Officer Applicants" (FIT CO) incorporated the on-the-job tasks from the PDA and the criterion forces. A physiological assessment and the ratings of subject matter experts confirmed the high validity of the FIT CO . Test-retest reliability (ICC = .997) was also demonstrated to be very high. FIT CO performance standards were established from the completion times of safe and efficient incumbent female COs. Although the FIT CO had no adverse impact on the pass rates of incumbent female COs, it was found that it could have an adverse impact on female CO applicants . This necessitated a consideration of accommodation. A training program was therefore undertaken with 40 general population females which resulted in an increased FIT CO pass rate from 32.5% to 82.5 %. This demonstrated that physical training provided the accommodation necessary to ameliorate any potential adverse impact. The FIT CO conforms to the BFOR Forum template and complies with the Meiorin requirements to qualify as a BFOR.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".