Governing solid waste management in Mazatenango, Guatemala: <i>Problems and prospects</i>
Bibliographic record
Abstract
Many smaller cities in developing countries are only beginning to plan for appropriate solid waste management systems. The majority of waste management systems in developing countries fail to address residents' sanitation needs properly. In this paper, we present the results of fieldwork in Mazatenango, Guatemala, examining the problems of governing solid waste, as linked to administration, collection, handling, and disposal. The problems identified include lack of adequate funding; no formal recycling programmes at the household level; absence of a sanitary landfill; increase of illegal dumping; limited public awareness of proper waste management practices; and street litter causing a breakdown in the sewer systems. The results of the study are used to propose strategies for improved governance of solid waste, addressing the needs and priorities of a range of stakeholders. These strategies highlight the importance of strengthening relationships among the stakeholders involved in the governmental/administrative, social, economic, and environmental aspects of solid waste management. The approach may be effective in other developing country cities that are starting to plan waste management systems.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".