opinions of Marine Stewardship Council certification
Bibliographic record
Abstract
As worldwide population growth continues to rise, so does demand for seafood by consumers. With this trend interest in sustainably certified seafood is also increasing. The Marine Stewardship Council (MSC) standard for sustainable and well-managed fisheries is considered the gold standard of fisheries certification worldwide. Because of fears that they may lose markets if they do not become certified, many fisheries in the U.S. and Canada, including the Maine lobster fishery, have recently begun to pursue MSC certification. Although certification provides a market-based incentive to improve sustainable fishing practices, it is a costly and time-consuming process, and often imposes additional requirements on fishing industries in order to meet certification standards. In order to evaluate whether the costs of certification of the Maine lobster fishery are worth the presumed benefits, I interviewed lobster industry members to learn about their knowledge and attitude towards MSC certification; administered an online consumer survey to understand consumers ’ attitudes and purchasing preferences related to ecolabeled lobster; and consulted with fisheries experts and representatives from other MSC-certified fisheries to compile lessons learned.
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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".