Assessing Ecological and Socio-Economic Attributes in Sustainable Management of Solid Medical Waste in Urban Environment
Bibliographic record
Abstract
Unreliable system of solid waste management has hindered performance of public health system in developing countries.This condition was exacerbated by the covid-19 pandemic which posed risk to healthcare staff and public that makes the management of medical waste worsening.This study seeks to analyze the existing conditions of community health centre solid medical waste management from ecological, economic and social aspects in Pekanbaru and to design a solid medical waste management model for community health centres in Pekanbaru by identifying and quantifying ecological and socio-economic attributes to help solid medical monitor waste.A mixed method approach is used in this study with inferential analysis.Data analysis was used to analyze the relationship of ecological, economic and social factors to the management of solid medical waste at community health centres in Pekanbaru.The analysis process included univariate and bivariate analysis using a computerized program.The findings show that monitoring through the waste monitoring application can help monitor waste management in community health centres.As an implication, a solid medical waste management model can be used and implemented to support sustainable solid medical waste management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".