A framework for qualitatively evaluating management plans in a results-based perspective
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Currently many multi-year management plans are being developed either for rebuilding depleted stocks or for avoiding difficult negotiations when management decisions must be revisited on a regular basis. Management plans are commonly evaluated by intensive model simulations that describe the ecological and economic dynamics, and the management loop. Under the resultsbased management paradigm, the fishing industry or particular fishing sectors will develop their own management plans, potentially leading to a huge number of plans to be evaluated. Guidelines for evaluating the plans on a qualitative level before launching quantitative evaluations will be essential. Here we propose a framework for evaluating management strategies in a qualitative way. A strategy is defined by i) an objective ii) a coordinated plan of actions to reach this objective. We evaluate i) under which assumptions the stated management objective is sustainable and ii) whether the proposed plan of actions can reach the objective, against theoretical criteria derived from general fishery models, and practical rules determining success of management plans from empirical review papers. We demonstrate this framework by analysing a series of management plans recently implemented in the EU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".