Defining Equity Criteria for Determining Fare Zones in Integrated Passenger Transport
Bibliographic record
Abstract
Fare system models in public transport are researched based on the fact that they represent a direct and flexible instrument of influencing passenger behavior and covering public transport costs, which contributes to the sustainability of public passenger transport. Integrated passenger transport, as a concept of public transport management that uses a zonal fare system, defines transport service prices within a fare zone. An analysis of existing fare systems reveals that current systems do not offer equitable access for passengers and that the transport service is not available to everyone. To resolve the issue of the transport disadvantage of potential passengers, society and space, fare system models must be changed to provide equity for disadvantaged participants of the system. This would do away with transport and social disadvantage in the analyzed region. The aim of this research is to define equity criteria in determining fare zones in integrated passenger transport. This is a precondition for an equitable fare model which would ensure an impartial and fair charge of transport services within zones.
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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 | 0.000 |
| 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".