Predicting the Likelihood that the United States will Implement Solar Radiation Management through an Analysis of Responses to Historical Crises
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
Given the lack of progress on effective policies to reduce greenhouse gas emissions, as well as the accumulating evidence that the earth is already experiencing the adverse effects of anthropogenic climate change, geoengineering has entered popular and technical discourses as a potential solution. As policy-makers, economists, scientists, engineers, and environmentalists consider various aspects of geoengineering, one of the questions that remains unanswered is how likely is it that humanity will engage in intentional actions to modify the global climate? This paper employs historical analysis to investigate the likelihood that American policy-makers will adopt solar radiation management techniques in order to control the global climate. Historical patterns of crisis response strongly suggest that policy-makers will follow similar decision-making patterns in the future.
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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 | 0.001 |
| 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) | 0.001 | 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