Fishery systems and linkages: from clockworks to soft watches
Bibliographic record
Abstract
Abstract Garcia, S. M., and Charles, A. T. 2007. Fishery systems and linkages: from clockworks to soft watches. – ICES Journal of Marine Science, 64: 580–587. The complex systemic nature of fisheries has been recognized for many decades, but attempts to include this reality in day-to-day management have been slow, patchy, and of limited effectiveness. The topic is reviewed again here, with a focus on new directions. After a brief introduction, an historical review is provided of the evolution of fisheries assessment and modelling, highlighting the growing complexity resulting from changing societal demands. The “complexity syndrome” is described in terms of scope, boundaries, scales, components, and linkages, and is demonstrated as reducing understanding, predictability, and controllability, attributable to the effects of delays, teleconnections, scale dependence, and self-organizational capacity. Key issues relate to systemic aspects of fisheries governance and the research needed to support it. Special reference is made to the changes needed to adapt to the newly emerging relationships between science, policy-making, and society within complex fishery systems, and between those systems and their environment. A range of concepts and approaches, such as Integrated Assessment, are elaborated as epistemological and operational frameworks to support the transition process. The conclusion addresses the evolution of the global fishery system and briefly reviews the challenges faced by science, governance, and society.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".