The relationship between general measures of fitness, passive range of motion and whole-body movement quality
Bibliographic record
Abstract
The goal of this study was to establish relationships between fitness (torso endurance, grip strength and pull-ups), hip range of motion (ROM) (extension, flexion, internal and external rotation) and movement quality in an occupational group with physical work demands. Fifty-three men from the emergency task force of a major city police force were investigated. The movement screen comprised standing and seated posture, gait, segmental spine motion and 14 tasks designed to challenge whole-body coordination. Relationships were established between each whole-body movement task, the measures of strength, endurance and ROM. In general, fitness and ROM were not strongly related to the movement quality of any task. This has implications for worker training, in that strategies developed to improve ROM or strength about a joint may not enhance movement quality. PRACTITIONER SUMMARY: Worker-centered injury prevention can be described as fitting workers to tasks by improving fitness and modifying movement patterns; however, the current results show weak correlations between strength, endurance and ROM, and the way individuals move. Therefore, the development of occupation-specific injury prevention strategies may require both fitness and movement-oriented objectives.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".