Postural Analysis of a Developing Country’s Municipal Solid Waste Handlers and a Reference Group of Hospital General Hands using the RULA Method
Bibliographic record
Abstract
BACKGROUND: Municipal solid waste handlers perform various work activities which may contribute to the onset of work-related musculoskeletal disorders (WRMDs). This study conducted a postural analysis of these workers and a reference group of hospital general hands in order to identify unsafe working postures requiring correction. METHODS: The Rapid Upper Limb Assessment (RULA) methodology was used for postural analysis to 30 municipal solid waste handlers (MSWHs) and a reference group of 30 hospital general hands (HGHs) involved in similar work activities. Field observations and photography were used to collect data. Collected data was analysed using STATA version 13.RESULTS: The Mann-Whitney test was used to compare the two groups. Results showed significant differences (p < 0.05) for lifting, carrying and emptying activities. For both groups, the mean postural scores for pushing, pulling and standing activities were mainly in the low risk category and not statistically significant (p > 0.05).CONCLUSION: Results of the present study show unsafe RULA postural scores to MSWHs with regard to lifting, carrying and emptying of refuse bins. Such scores are suggestive of an elevated risk to developing WRMDs in these workers compared to the reference group.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".