Refining the Evidence: British Columbia’s Carbon Tax and Household Gasoline Consumption
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The impact of carbon prices on consumer behavior is a central element in current policy debates dealing with mitigation of greenhouse gas emissions. We examine the impact of British Columbia’s carbon tax on private automobile gasoline use.We control for several factors that influenced gasoline demand during our study period, including local public transit improvements and increased cross-border shopping. Our results suggest that a 5 cent per litre carbon tax reduced gasoline consumption by 8%. We find that households residing in Vancouver and other cities responded to the carbon tax, whereas households in small towns and rural areas did not respond. We perform several sensitivity analyses. Even our most conservative lower bound estimate suggests that a 5 cent per litre carbon tax reduced gasoline consumption by 5%.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it