Integrating equity-focused planning into coral bleaching management
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
Abstract Coral bleaching, associated with warm water temperatures of the oceans, represents the most significant threat to coral reef ecosystems and coastal communities regarding climate change. Coral bleaching prediction models have emerged as essential tools in conservation and policy-making. However, the effectiveness of these models as an equity-focused science-policy nexus remains uncertain when local human community perspectives are disregarded. This paper presents an equity-focused framework for coral bleaching prediction and response, integrating local goals and contexts. We discuss the equity gaps during coral bleaching assessments while emphasizing the importance of early warning systems in promoting and facilitating more accurate reporting of bleaching episodes. Additionally, this research also highlights the complex but inherent interactions of multiple drivers, underscoring the need for cautious and socially inclusive strategies for climate adaptation. This perspective paper advocates for an equitable approach in science-policy networks to support the preservation of coral reefs while safeguarding the well-being of reef-related coastal communities.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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