Finding logic models for sustainable marine development that deliver on social equity
Bibliographic record
Abstract
Sustainable development is often represented as contributing to desirable outcomes across economic, environmental, and social goals, yet policies and interventions attempting to deliver sustainable development often disagree on the order in which these categories of goals should be addressed. In this Essay, we identify and review 5 approaches (called logic models) for sustainable development in ocean systems based on existing policies and interventions and consider the evidence for their contributions to equity-the ultimate goal of sustainable development according to the UN Sustainable Development Goals (SDGs). Two of the 5 logic models prioritize economic growth and lead to social and environmental benefits, 2 prioritize environmental health as a prerequisite for sustainable economic and social benefits, and the final logic model is community driven and prioritizes social dimensions. Looking towards the 2030 maturation of the SDGs, we will need to understand what models are best suited to deliver on equity gains and prevent future inequities in development and how best to operationalize them.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.010 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".