Perspectives on the externalities of road usage in South Africa
Bibliographic record
Abstract
A perspective on the externalities of road usage in South Africa is discussed. The road system and road users are causing enormous positive externalities to society. These include access to economic activities, health services, education, retail facilities, and recreation. Road users pay a variety of taxes and levies to the state, such as VAT on vehicle sales, VAT on vehicle part sales/car repair services, import duties on vehicles/parts, and fines. A report for Cape Town reveals that the two major routes in the city, N1 and N2, experience heavy congestion every weekday, which could equal 50% of all congestion in the city. A recent report on congestion costs for Canada reveals that more than 90% of this cost is time lost in traffic by drivers and passengers, 7% is attributable to increased fuel consumption and 3% is attributable to green house gas emissions under congested conditions. The positive external value of the road network is estimated to be in excess of R150 billion per annum and by far exceeds the negative externalities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".