Marine Social Science for the Peopled Seas
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
Coastal communities, indigenous peoples, and small-scale fishers rely on the ocean for livelihoods, for subsistence, for wellbeing and for cultural continuity. Thus, understanding the human dimensions of the world’s peopled seas and coasts is fundamental to evidence-based decision-making across marine policy realms, including marine conservation, marine spatial planning, fisheries management, the blue economy and climate adaptation. This perspective article contends that the marine social sciences must inform the pursuit of sustainable oceans. To this end, the article introduces this burgeoning field and briefly reviews the insights that social science can offer to guide ocean and coastal policy and management. The upcoming United Nations Decade of Ocean Science for Sustainable Development (2021–2030) provides a tremendous opportunity to build on the current interest, need for and momentum in the marine social sciences. We will be missing the boat if the marine social sciences do not form an integral and substantial part of the mandate and investments of this global ocean science for sustainability initiative.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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