Eco-certification, assessments, and advice: implications of market measures for traditional practices
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The eco-certification standards necessary to be consistent with international guidelines from the FAO greatly expand the factors to be considered in “assessing” a stock and fishery. The actual assessments are done by small panels of selected experts, and it is fisheries and not States that formally request certification (and the assessments required to be certified). Nonetheless, the panel assessments are in large part critical reviews of work submitted by the applicant(s) for certification. The analytical work traditionally associated with a “fishery assessment” will usually have been done by agencies or under contract. To the extent that States in support of their fisheries or the fisheries themselves want to use traditional sources of science advice as the basis for their submissions of “assessments” to the expert panels doing the certification evaluations, the ecocertification standards require the traditional contents of an “assessment” to be reviewed. In this paper, experience with both the ICES and Canadian fisheries and ecosystem assessment processes and with several eco-certification evaluation panels is applied as a basis for such a review. The P1 Marine Stewardship Council (MSC) certification standards deal with the status of the target species of the fishery and the direct impacts of the fishery on the target species. The P2 standards deal with the impact of the fishery on the ecosystem in general. For P1 the degree to which “standard assessment practice” produces results that are sufficient for an eco-certification assessment against P1 is considered. For P2, what an “ecosystem assessment” would have to address in order to be sufficient to inform a certification panel regarding the sustainability of impacts of a fishery relative to the ecosystem is outlined.
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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 | 0.116 | 0.226 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.028 | 0.040 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.027 | 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".