Challenges faced by small-bus operators in participating in the formal public transport system
Bibliographic record
Abstract
Background: Small-bus operators (SBOs) in South Africa operate on the periphery of the economic mainstream of scheduled subsidised commuter transport, and little progress has been made in getting these operators into the more formal subsidised industry. There is also a lack of information about the challenges these operators face in participating in the public transport industry.Objectives of the research: The main objective of the research was to conduct a survey among SBOs to obtain a better understanding of the challenges that they face in participating in the public transport industry.Method: A telephone survey of operators was undertaken to ensure an adequate response to a structured questionnaire. In analysing the data, we made use of Factor Analysis and the Statistical Package for the Social Sciences (SPSS) to undertake general statistical analysis.Results: The main results of the survey indicate that SBOs face significant financial and operational challenges. There is also a perceived lack of government support for SBOs. Major conclusions are that the Department of Transport (DoT) ought to address issues related to the complex governmental reporting and legal requirements for small business. In addition, government ought to be creating ‘space’ for SBOs in the design of contracts and actively encouraging the formation of consortia’s or partnerships, among the SBOs and/or between SBOs and established bus companies. Government, and especially the DoT, ought to more actively market the governments’ small-business support systems and procedures together with financial aid schemes to assist SBOs in acquiring or replacing buses.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".