Comparative Economic Analysis of Conventional and Plug-in Battery Electric Vehicles in Canada
Bibliographic record
Abstract
Conventional vehicles typically use gasoline for their internal combustion engines (ICEs). On the other hand, plug-in battery electric vehicles (PBEVs) use electricity to charge their batteries, and hence they do not need gasoline. With the soaring gasoline prices in Canada and around the world, the interest in electric vehicles from the public and the government has increased. However, given the wide range in prices of PBEVs, the high maintenance cost of conventional vehicles and the volatility in gasoline prices, there is a need for a comparative economic analysis to address the following two main questions: (1) What should be the minimum ownership period of a PBEV to be economical than a conventional vehicle? (2) At what gasoline prices do the PBEVs become more economical than conventional vehicles? The work in this paper addresses these questions to assist customers in making the right decision when they intend to purchase a new vehicle. The results have shown that the longer the ownership period is, the PBEVs become more economical compared to conventional vehicles. The study has shown that the total ownership cost savings may reach up to $88,482 over 15 years.
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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 | 0.000 | 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 | 0.000 |
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".