Public transport policy implementation in South Africa: <i>Quo vadis</i>?
Bibliographic record
Abstract
For many years the South African government has put forward policies and strategies to improve and promote public transport. Despite this, very little has changed over the last 30 years, although projects such as the Gautrain high-speed rail service and a few bus rapid transit routes have been introduced recently. These projects, however, are not integrated in a logical manner into the broader public transport system and are often referred to as stand alone interventions because of a lack of managing public transport in terms of integrated transport plans. The traditional commuter rail, bus and 16-seat taxi industries therefore operate in policy silos and, in the case of the bus and rail industries, are planned and funded independently of each other, leading to a further lack of integration. Policy interventions have been implemented partially or not at all, leaving the public transport sector in a state of flux. The methodology followed in researching this paper was to briefly trace the historical public transport policy developments, with a focus on the commuter bus industry, in order to identify possible impediments to policy implementation and to identify policy interventions for addressing the currently stalled policy implementation programme. The main finding of the paper is that it would be advisable to establish provincial transport authorities between local and provincial governments. That should speed up the development and implementation of integrated transport plans, which ought to lead to integrated public transport systems and a more optimal spend of the available governmental funds aimed at subsidising 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".