Identification and characterization of the critical physically demanding tasks encountered by correctional officers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this investigation was to identify the critical tasks encountered by correctional officers (COs) on the job and to conduct a comprehensive assessment and characterization of the physical demands of these tasks. These are the first steps in developing a fitness screening test for COs in compliance with recent legislation. The most important, physically demanding, and frequently occurring tasks were identified using Delphi methodology, focus groups, and questionnaire responses from 190 experienced front-line COs. These tasks were structured into emergency response scenarios for which a physical and physiological characterization was conducted to verify their relative physical demands analysis. Oxygen consumption and the forces exerted by COs were quantified while they were responding and then controlling and restraining inmates. The female COs used less force than the male COs did to control and restrain the same inmates (body control = 46 vs. 60 kg, wrist hold = 32 vs. 49 kg, and arm retraction = 37 vs. 47 kg) and did not exert their maximal strength during their control and restraint activities. The mean oxygen consumption of the female and male COs while performing the on-the-job tasks was similar (39.5 vs. 38.5 mL.kg-1.min-1). We concluded that the essential components of a fitness screening protocol for CO applicants are cell search, expeditious response, body control, arm restraint, inmate relocation, and an assessment of aerobic fitness. The criterion performance standards for completing these tasks in a circuit were set at the job performance level of safe and efficient female COs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it