Fitness components associated with performance of a law enforcement physical employment standard in police cadets
Bibliographic record
Abstract
BACKGROUND: The physical preparation of cadets for both physical employment standards (PES) and police job performance is a major concern for police organizations. Identifying fitness components associated with both PES performance and work performance can provide essential information for the physical training of police cadets. Therefore, the objective of this study was to assess the association of fitness components with performance of the Standardized Physical Abilities Test (SPAT), a new law enforcement PES.METHODS: A sample of 41 police cadets was recruited to take part in this cross-sectional study. First, the participants were assessed using six fitness assessments (standing broad jump, medicine ball put, grip strength test, visuomotor reaction time (VMRT) test, modified agility T-test, and 600-meter run). In a second experiment, participants performed the SPAT.RESULTS: Bivariate correlation analysis showed moderate to strong associations between each fitness assessment and SPAT performance. Based on stepwise multiple regression analysis, results at the VMRT Test, the medicine ball put, and the agility T-test accounted for 66.0% of the variability in SPAT performance (R2=0.660; P<0.001).CONCLUSIONS: Overall, our results suggest that exercise prescriptions for police cadets should focus on power, agility, and VMRT. Furthermore, our results show that performance in a PES can be estimated rather precisely based on low-cost fitness assessments. Therefore, such methodology could be used to develop fitness assessments specific to PES requirements.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".