Just Transition and Social Acceptability: A Canadian Case
Bibliographic record
Abstract
This paper takes place at the intersection of climate policy, public opinion and the ‘just transition’ debate. Its central hypothesis is: the inclusion of fairness measures in the green economy transition – especially by targeting workers in the most affected sectors – will have a positive impact on the social acceptability of climate policy. This paper focuses on two key policies: carbon pricing and a fossil fuel phase-out. A set of survey questions compare social support for these two policies (i) without and (ii) with accompanying fairness provisions, such as green jobs creation and support for workers. This paper uses an exclusive survey (n = 1,500) conducted in Canada in 2022. From the data, we observed that fairness provisions increase the support both for a higher price on carbon and for a decrease in the production of oil and gas, which was especially salient for groups initially less concerned by climate change.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.041 | 0.025 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".