Perception of printing workers regarding occupational health hazards and safety measures
Bibliographic record
Abstract
Background and objective: Printing workers are frequently exposed to many forms of occupational hazards while doing their jobs. Little research was done in Egypt about printings occupational hazards, which constitute a huge burden on the affected workers and employment settings. Therefore, the present study aimed to investigate the perception of occupational hazards and safety measures among printing workers.Methods: Descriptive analytic design was carried out the current study at the Egyptian Book House Press in Cairo on a purposive sample of 200 workers using a structured questionnaire to collect data, which include demographic data, occupational hazards, predisposing factors and safety measures as perceived by workers.Results: The results revealed that the majority of workers exposed to moderate level of occupational health hazards and safety measures. The most hazards the printing workers are exposed to it, are health, chemical, injury and psychological hazards. Also, there is a highly statistically significant negative correlation with total occupational hazards and safety measures.Conclusions: The study can be concluded that the workers exposed to moderate occupational hazards. As well, the majority of workers stated that there is a moderate level of safety measures to occupational hazards in their workplace. Therefore, this study recommended that continuous training of the printing workers on safety guidelines and enforcement of standard safety practices to decrease the potential occupational hazards.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".