Exploring Ocean-related Rights in a Transforming World
Bibliographic record
Abstract
Rights-based approaches are proving pivotal as we struggle with the challenges around biodiversity loss and ecosystem degradation. Human rights span a broad spectrum from individual and community-based rights to national and global human rights to healthy oceans, which includes access. Rights of Nature, implicit in many Indigenous communities, have seen growing recognition in recent decades and, in several instances, personhood of nature/parts thereof have been granted legal standing. This introduces a new dimension to management of ocean-based anthropogenic activities. In this paper, we examine potential synergies and trade-offs when aiming for a balance between human rights and ocean-related nature’s rights as we strive towards more desirable futures. We focus on rights-based approaches in managing human-nature interactions in the ocean context, including visions that have been developed and visioning processes that have been undertaken, with a view to transforming ocean-human inter-relations and coexistence.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".