Energy and Environmental Policy Trends: Emissions Pricing and Affordability: Lessons from British Columbia
Bibliographic record
Abstract
How does emissions pricing affect affordability in Canada?BC, with the longest-running carbon tax, offers some lessons.Some blame emissions pricing for increasing costs and decreasing energy affordability.Concerns about affordability in Atlantic Canada even prompted the Government of Canada to exempt heating oil from the federal fuel charge until March 31, 2027.Emissions pricing affects households' costs in two ways.First, it directly increases the price of fuels based on the amount of CO2 emitted as they are burned.The 2023 price is $65 per tonne, which translates into 14.3 cents per litre of gasoline and $3.32 per GJ of natural gas.Second, increases in the price of fossil fuels -gasoline, diesel, natural gas, heating oil etc. -trickle through the supply chain, indirectly raising the price of goods and services across the economy and so increasing households' costs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".