Smart transportation and the economic effects of the Quebec-California caps and trade market
Bibliographic record
Abstract
There is an increasing trend in the demand for electric vehicles (EV) but consumer choice is very limited compared to the gamut of conventional cars. The demand for the latter is still growing despite their negative impact on the environment and government policies to incentivise the reduction of their use. This paper examines the consumption patterns of the Canadian commuters who travel by car. It estimates the demand for car transportation services for the province of Quebec and makes simulations to predict the evolution of this demand till the year 2040. The estimations of the 'baseline scenario' are made using some key variables such as car price, annual kilometres driven, and the price of substitutes such as public transit. In the first simulation, there is no government intervention to modify the consumption patterns of drivers. A second model is used to investigate the impact of the pollution permits on the demand for vehicles. The new Quebec-California caps and trade (C&T) market is analysed and its impact on the demand for cars and the environment is empirically estimated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".