Policy innovation through local, sustainable development evaluation
Bibliographic record
Abstract
The global political agenda has included some high-profile environmental summits over the past few months. Three of these events stand out. The 2022 United Nations (UN) Climate Change Conference in Sharm el-Sheikh, Egypt, was held from 6–20 November 2022. This was followed from 7–19 December 2022 by the UN Biodiversity Conference in Montréal, Canada, and the UN-Water Summit at UN Headquarters in New York City from 22–24 March 2023. Of these three events, the Biodiversity Summit made the most impact as delegates committed to protecting 30% of land and 30% of coastal and marine areas by 2030. This pledge is remarkable because it re-establishes political commitments to protect biodiversity, which is a key component of climate action. At the same time, many observers of the summit questioned how nation-states will implement this goal. Like the SDGs, the “30 by 30” commitment is long on aspirations but short on operationalization details. This observation is not a criticism of the agreement per se but a recognition of the challenges preventing ambitious biodiversity conservation plans from being fully implemented.
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.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".