The Pushback Against Canada’s Carbon Pricing System: A Case Study of Two Canadian Provinces, Saskatchewan and Nova Scotia
Bibliographic record
Abstract
As part of its plan to transition to an energy secure and environmentally sustainable future, Canada has had a national carbon pricing system since 2019. When first introduced, the $20 (‘$’ refer to Canadian dollars (CAD) in this paper) per tonne price was widely accepted by most Canadians and seen as a way of helping Canada meet its emissions reduction pledges made at the 2015 United Nations Climate Change Conference (COP 21) in Paris. The Canadian system is novel in that it both charges consumers for their emissions and reimburses them for their expected emissions; this is intended to raise awareness of their emissions and encourage those who can afford to opt for lower-emissions energy services to do so. By 2023, the combination of the carbon price reaching $65 per tonne and the post-pandemic economic slowdown was seized on by numerous politicians as a way of pushing back against the carbon pricing system, with most demanding the entire system be scrapped. The debate intensified in late 2023 and into 2024, when the federal government removed the carbon tax on home heating oil because the reimbursement was insufficient to cover the cost of the tax. In this paper, we consider the recent actions of two Canadian provinces, Saskatchewan and Nova Scotia, embroiled in the federal carbon pricing system debate due to the removal of the carbon tax on fuel oil for space heating. The objective of this paper is to identify how some of the reasons, including global post-pandemic inflation and other challenges facing Canadians, such as those cited in third-party polls, have contributed to a rise in the system’s unpopularity. Our method estimates and compares the impacts of the carbon tax on the household energy services for space and water heating, lighting and appliances, and private (i.e., household) transportation for different types of housing (apartment, single-attached, and single-detached) and number of occupants (two, three, and four) in Saskatchewan and Nova Scotia. The results of this work show that while Saskatchewan households have higher energy intensities than those in Nova Scotia, the impact of the carbon tax on Nova Scotians using fuel oil for heating was greater than in Saskatchewan. In Saskatchewan and Nova Scotia, natural gas and electricity, respectively, are used for heating. This paper concludes with a summary of our findings and potential options for improving perceptions of the system.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.023 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".