Bibliographic record
Abstract
Abstract International climate change diplomacy has tried a rigid top-down approach (the Kyoto Agreement) and a more flexible bottom-up approach (the Paris Agreement). Neither approach has gained sufficient traction on the climate change problem. The authors of Fixing the Climate: Strategies for an Uncertain World propose a new direction. Borrowing from the framework of the Montreal Protocol of 1987, which made great strides in eliminating use of ozone-depleting chemicals, they outline a framework for “experimentalist governance” that relies on public and private organizations to promote a problem-solving approach that is, at the same time, both bottom-up and top-down, market based and institution based, technocratic and democratic. Using case studies and examples across a wide array of contexts—from U.S. coal-fired power-plant sulfur dioxide emissions to dairy farm pollution in Ireland—they build the case for infusing climate change governance with innovation-driven institutions, processes, and instruments. The case studies and examples, however, share several common features that suggest experimentalist governance thrives under ideal conditions, including clearly defined technology challenges and ability to contain the impacts of innovation largely to the incumbent industry. Under the Montreal Protocol, for example, switching chemicals in products did not require consumers to change behavior or make substantial sacrifices. Many of the challenges of climate change policy fit these and the other ideal conditions, but many do not. The full extent of the necessary energy transition, as well as the demands of climate change adaptation, present complex socioeconomic policy issues fraught with political division. Experimentalist governance can go a long way toward fixing the climate, but ultimately, fixing the climate also will require fixing the climate politics.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.150 | 0.038 |
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".