Self-reinforcing and self-undermining feedbacks in subnational climate policy implementation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study demonstrates how interpretive feedback functions as an intervening mechanism during policy implementation that helps explain variation in subnational climate policy entrenchment. We examine three interrelated climate policy processes in Ontario, Canada from 2001–2018: a coal phase-out (2001–2014), the feed-in-tarriff (FIT) program for renewable energy (2006–2013) and a cap-and-trade program (2008–2018). Successful framing of the coal phase-out in terms of gains for both public health and climate change helped generate a broad-based coalition of support during implementation. Conversely, we find that the FIT and the cap-and-trade programs were vulnerable to framing around losses, especially regarding electricity rates and household costs, which counter-coalitions used to weaken public support during implementation. Our analysis demonstrates that building supportive coalitions for climate policy goes beyond the material gains and losses generated by initial policy designs. Framing strategies interact with policy designs over time to support or undermine policy durability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it