ENVIRONMENT-BASED DESIGN (EBD) APPROACH TO IDENTIFY CRITICAL ISSUES IN MANAGING MUNICIPAL SOLID WASTE: NAIROBI, KENYAN CASE STUDY
Bibliographic record
Abstract
Abstract. As the urban population grows and the global economy develops, municipal solid waste management (MSWM) has become an increasingly prominent global issue. MSWM is particularly difficult in developing countries due to its high cost and time-consuming nature. The Environment-based design (EBD) can potentially contribute to global MSWM by reducing costs and increasing efficiency, especially in helping developing countries identify critical issues in MSWM. This paper uses and demonstrates the effectiveness and efficiency of the EBD method to analyze and identify critical issues in MSWM, using the city of Nairobi as a case study. This paper contains the first two of EBD's three activities: environment analysis and conflict identification, during the design problem period, design knowledge, and design solutions simultaneously and interdependently evolve as a part of the environment. The comparison with the existing literature confirms that the conclusions reached are, to some extent, reliable, time-saving, and less costly, which will offer a possibility to solve the problem of MSWM in impoverished areas.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".