Institutional complexity and private authority in global climate governance: the cases of climate engineering, REDD+ and short-lived climate pollutants
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
How and why do institutional architectures, and the roles of private institutions therein, differ across separate areas of climate governance? Here, institutional complexity is explained in terms of the problem-structural characteristics of an issue area and the associated demand for, and supply of, private authority. These characteristics can help explain the degree of centrality of intergovernmental institutions, as well as the distribution of governance functions between these and private governance institutions. This framework is applied to three emerging areas of climate governance: reducing emissions from deforestation and forest degradation (REDD+), short-lived climate pollutants (SLCPs) and climate engineering. Conflicts over means and values, as well as over relatively and absolutely assessed goods, lead to considerable variations in the emergence and roles of private institutions across these three cases.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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