Bibliographic record
Abstract
Preferences for transport activities are often considered only in terms of time and money. Whilst congestion in automobile traffic increases costs by raising trip durations, the same is less obvious in public transport (PT), especially rail-based. This has lead many economic analyses to conclude that there exists a free lunch by reducing the attractiveness of automobile transport at no (or little) cost for PT users. This article argues that congestion in PT - crowding - is also costly. Using survey data from the Paris metro we estimate the degree to which users value comfort in terms of less crowding. Using a contingent valuation method (CVM) we describe marginal willingness to pay over different parts of the distribution of in-vehicle crowding and consider moderating factors. We conclude that the total welfare cost for a trip rises from ¤2.42 for a seated passenger to ¤3.69 under the most congested conditions. We apply our results to the cost-benefit analysis of a recent investment in PT in Paris and consider broader implications for transport policy. In particular, we highlight that PT congestion is a first-order urban externality. Evaluation of non-market goods, crowding costs, contingent valuation method
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".