SEA, Urban Plans and Solid Waste Management in Kenya: Participation and Learning for Sustainable Cities
Bibliographic record
Abstract
This paper examines the role of participation and learning in Kenyan strategic environmental assessments (SEAs) of urban plans that include a solid waste management (SWM) component. Two SEA cases were studied using 40 semi-structured interviews and two focus groups. Data are analysed qualitatively employing NVivo software. Participation is assessed using ideal conditions of learning derived from Transformative Learning Theory, and operationalised for this study. Strengths of SEA participation are freedom from coercion and equal opportunity to participate. Notable weaknesses include inaccessibility of SEA documents, inadequate participant funding, and lack of feedback and transparency about the SEA findings. Participants exhibited numerous learning outcomes and associated social actions on urban SWM including waste sorting, recycling and composting (instrumental learning), sharing values and community collaborations on cleanup and recycling (communicative learning), and altering conventional viewpoints from ‘waste for disposal’ to ‘waste as a resource’ (transformative learning), including for livelihood opportunities.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".