Effectiveness of health and safety training for municipal waste collectors: a case study from Galle, Sri Lanka
Bibliographic record
Abstract
Municipal waste collectors are exposed to numerous hazardous substances during the process of collection, transportation and the disposal of municipal solid wastes, resulting in occupational health and safety risks including mortality and morbidity. An efficient and safe municipal solid waste collection system is vital to protect the environment, the community and the workers involved. Therefore, a training module was developed based on the needs analysis, and after conducting a series of training and awareness programmes, personal protective equipment was distributed to all the 115 municipal waste collectors in Galle Municipal Council, the provincial capital of Southern Province of Sri Lanka. The objective of this study was to determine the effectiveness of those project interventions. A questionnaire survey, key informant discussions and expert observations were used as primary data collection tools, while secondary data were gathered from various reports. Knowledge, Attitudes, Practices (KAP) questionnaire was used to evaluate the conditions of 115 municipal waste collectors before and after conducting the training programme and distributing the personal protective equipment. The interventions made by conducting the training programme described in this study had effectively created a significant improvement in knowledge, attitude and practices of the respondents (p < 0.05). Personal protective equipment distributed has resulted in an increase of dignity among the waste collectors giving them recognition by both Galle Municipal Council and the general public of the area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".