A Stated Preference Study to Explore Market-Based Instruments to Reduce Car Usage
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Car dependency is becoming an increasingly difficult problem for policymakers to contend with, and requires targeted policy solutions that balance the need for greater urban mobility with reduced congestion. We investigated public preferences for welfare measures designed to encourage car use reduction and promote more sustainable urban environments. Cross-sectional survey data were obtained from n = 773 car owners living in Belfast, United Kingdom. A discrete choice experiment was used to elicit the willingness-to-pay (WTP) for a congestion charge that would finance policies to reduce car usage. A contingent valuation question assessed the willingness-to-accept (WTA) a monetary incentive to reduce car usage. WTP values were computed using a mixed logit model, and an interval data model was used to assess the factors that were correlated with WTA. We also calculated the benefit to the economy of reduced car usage. WTP for different policy measures ranged from £2.12 to £11. The highest WTP value was observed for improvements to public transport frequency, coverage, and connectivity. The median WTA value to reduce car usage by one day per week was £3. As a result of reduced emissions and road casualties, it was estimated that this intervention would generate benefits worth £3.83 m, however this was greatly outweighed by the costs involved.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it