Review of Management Plan Conservation Strategiesfor Canadian Fisheries on Georges Bank:A Test of a Practical Ecosystem-Based Framework
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The word 'based' in ecosystem-based management explicitly acknowledges that ecosystems are not managed. Rather, human use activities that impact those ecosystems are managed. Making ecosystem-based management operational involves converting broad conservation objectives for productivity, biodiversity and habitat into explicit strategies, whose performance can be measured by indicators, for regulating those human use activities. The fisheries management plan strategies used to achieve the conservation objectives for ecosystem-based management of Canadian fisheries on Georges Bank were reviewed to a) determine the degree to which existing management plans address the conservation objectives, b) evaluate how the plans have performed with respect to these strategies and c) provide a synthesis of aggregate results and consideration of cumulative effects across management plans for an area. Four fisheries management plans govern Canadian fishing activity on Georges Bank, those for groundfish, herring, scallop and lobster/Jonah crab. The plans focus on strategies aimed at sustaining population productivity for the utilized resources. Community productivity is considered to be adequately addressed by moderating exploitation on the utilized species. Biodiversity concerns are addressed through bycatch limitations for incidental mortality and through restricted fishing zones. Habitat considerations, other than those related to preserving biotopes, have not featured prominently. The plans reflect the historical emphasis by fisheries science and management on the broad conservation themes, with population productivity studies dominating through most of the 20th century, incidental mortality receiving attention in the latter decades and habitat considerations emerging as the most recent concern.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.019 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".