Designing Procedural Mechanisms for the Governance of Solar Radiation Management Field Experiments: Workshop Report
Bibliographic record
Abstract
The unexpected ocean fertilization experiment off the west coast of Canada in 2012 highlights the reality that non-governmental actors can already initiate small- to medium-scale environmental experiments and solar radiation management (SRM) field experiments with no government funding or approval. Without careful consideration and development of a governance framework for these types of experimentation, governments could be caught out having to respond ad hoc to situations driven by non-governmental actors.\n\nThis two-day workshop considered and evaluated governance mechanisms that may be useful for managing proposed SRM field experiments. Two specific procedural mechanisms were under consideration: environmental impact assessments and research registries. To ensure discussions were as realistic as possible, participants used a set of recently published SRM field experiment proposals as hypothetical examples when considering and evaluating both mechanisms. The workshop operated under the Chatham House Rule, and no attempts were made to forge consensus positions or to generate policy recommendations. Rather, this workshop was exploratory in nature, with discussions ranging widely along with personal opinions on some topics.
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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 | 0.170 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".