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
Abstract Political scientists Alexander Gazmararian and Dustin Tingley's incisive new book Uncertain Futures: How to Unlock the Climate Impasse contends that credibility is key to unlocking the deadlock over climate policy. They claim that fossil fuel communities have often been skeptical of any transition away from fossil fuels with good reason. In similar situations, policymakers have often failed to follow through on policies meant to mitigate economic dislocation. Drawing on a wealth of quantitative and qualitative evidence from energy-producing communities, including surveys of residents and officials alike, Gazmararian and Tingley find that different policy features that bolster credibility can build support for a transition to clean energy sources. The book provides a much-needed view of the energy transition from the ground-up. Yet the book pays less attention to a principal-agent problem at the heart of the clean energy transition: many of the elected representatives of the communities most affected by the transition don’t acknowledge any need for a transition. What's more, in a highly polarized environment, the impact of policy feedbacks is likely to be muted. Drawing on the experiences of the ACA and Canada's carbon tax, we suggest that even when the policy features that the authors propose are present, support for clean-energy policies may not rise dramatically.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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