Managing marine resources sustainably – Ecological, societal and governance connectivity, coherence and equivalence in complex marine transboundary regions
Bibliographic record
Abstract
This overview proposes a novel typology of characteristics required to ensure that marine assessment and management is connected, coherent and/or equivalent across boundaries, both within or between national and international jurisdictions. This defines the types of connectivity, coherence nature and equivalences with their relevance and examples in a marine transboundary context. It indicates the way of identifying impediments to be addressed to ensure that the management across marine boundaries is sustainable and adequate, and it also gives examples of the way of overcoming those barriers. The typology covers natural environmental, governance (policies, politics, administration and legislation), economic and management regimes. It encompasses sector (e.g. fishing, navigation, etc.) and their activity-, pressures-, effects- and management response-footprints and Maritime Spatial Planning and Marine Protected Area-designation. This links monitoring, assessment and reporting across boundaries and within the physico-chemical and ecological realms and in marine conservation across boundaries. Finally, it shows connectivity, coherence and equivalence should reflect wider societal and cultural aspects as well as governance approaches, principles and outcomes in adjacent countries (States) and regions. These aspects are summarised by analysing the so-called 10-tenets for sustainable and successful marine management. Although this typology is developed largely from a European and North America perspective, it is proposed here for validating with examples in other areas worldwide.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".