Who is Right to Fish? Evolving a Social Contract for Ethical Fisheries
Bibliographic record
Abstract
Most debates on government fisheries management, focusing on dramatic fishery collapses, have skirted the ethical dimension implicit in the exploitation, for private gain, of fishery resources that are publicly owned. The privilege to fish, a conditional right often nefariously perceived as a legislated "right," implies ethical responsibilities linked to marine stewardship. To date, however, granting this privilege to fish has not been legally tethered to the fiduciary responsibilities of businesses to their clients or governments to their citizens: sustainable management of fisheries and conservation of living marine resources. Legal rights must be coupled with moral responsibilities if governments, private fishing enterprises, and civil society are to conserve marine resources for present and future generations. Evolving a social contract for ethical fisheries that explicitly mandates collaborative governance and corporate responsibility can protect public goods and society's right to fish, both to eat and to exist in the sea.
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 | 0.052 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.068 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".