Multi-stakeholder dialogue on formal and informal forms of public transport in Harare, Zimbabwe: Convergence or divergence perspective
Bibliographic record
Abstract
Cities in the developing world are growing both geographically and demographically. Thisgrowth has increased pressure on services, including the public transport systems used bythe majority of people. In the last two decades public transport provision has undergoneconsiderable changes. Concomitant to these changes there has been debate on the formof public transport to be operated. Such debate has been informal, general, and at timesacademic, and therefore not able to provide substantive understanding of the views of keystakeholders. Zimbabwe has had an explosion of informal transport activity in the formof minibuses, and decision makers appear to be in a policy dilemma because of a need tostrike a balance between maximising passenger welfare whilst protecting the livelihoods ofindigenous minibus operators and striving to build an efficient and environmentally soundurban transport system. Critical questions for policy dialogue in this conundrum include,inter alia: How do stakeholders perceive the current public transport system? How can publictransport be sustainably provided? This study seeks to answer these questions using a casestudy of Harare. A qualitative research approach blended with some quantitative aspects wasused. Initial steps involved the identification and clustering of key urban public passengertransport stakeholders, followed by structured and unstructured interviews. Although thereis lack of consensus on the form of public transport that the City of Harare should adopt, thereis a strong view that a mass transit system is the backbone of sustainable public transport.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.021 | 0.022 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".