A Systems Approach Framework for Coastal Zones
Bibliographic record
Abstract
This Special Feature Volume examines the potential value of the Systems Approach Framework (SAF) as a methodological framework for the transition to sustainable development in coastal zones.This article provides insight on the Systems Approach, the theory behind it, and how its practical application to coastal zone systems (CZSs) was developed.The SAF is about information for management through a focus on how to generate a higher, dynamic level of information about complex CZSs and how to render this information more useful to end users through a participatory suite of communication methods.The SAF is an open research methodology that investigates the function of systems in order to simulate specific issues or questions concerning their function.The research articles that are included in this Volume demonstrate examples of coupled multidisciplinary methods integrated into SAF simulations appropriate to a selected policy issue and to the social-environmental conditions of each Study Site Application.Their findings are not the result of funded research projects; instead, they are byproducts of pilot applications conducted to develop and improve the SAF methodology.The final article of this Volume synthesizes these results in the context of the SAF as a higher level instrument for integrated coastal zone management.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".