Comparison of ergonomic risk factors and work-related musculoskeletal disorders among dismantler and burners of electronic waste in Agbogbloshie, Accra Ghana
Bibliographic record
Abstract
Rudimentary methods for electronic waste (e-waste) recycling employed in developing countries are a source of work-related musculoskeletal disorders (WRMSDs). A summarized comparison of WRMSDs and preliminary exposure assessment among e-waste dismantlers (D) and burners (B) in Agbogbloshie, Ghana is presented. A cross-sectional study was conducted to investigate WRMSDs and associated risk factors using the Cornell Musculoskeletal Discomfort Questionnaire and a newly developed ergonomic assessment tool. Results indicated higher WRMSDs prevalence in the lower back (68% D vs. 52% B; p = 0.172), shoulder (41% D vs. 29% B; p = 0.279) and upper arm (33% D vs 5% B; p = 0.010). Moderate to severe trunk flexion, high force exertion, repetition and vibration were prevalent risk factors among workers and were significantly higher in dismantlers than burners ( p ≤ 0.001). Detailed ergonomic studies investigating the relationship between physical exposures and WRMSDs are needed to provide a deeper understanding of WRMSD causation in e-waste workers and more particularly in unstructured, unregulated work.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".