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Record W4410968924 · doi:10.1038/s44183-025-00130-9

Rethinking maritime security from the bottom up: Four principles to broaden perspectives and centre humans and ecosystems

2025· article· en· W4410968924 on OpenAlexaff
Michael Fabinyi, Christopher Cvitanovic, Kate Barclay, Nathan Bennett, Edward Sing Yue Chan, Hanh Nguyen, Stefan Partelow, Annie Young Song, Natasha Stacey, Dirk J. Steenbergen, Bianca Suarez, Maria Tanyag

Bibliographic record

Venuenpj Ocean Sustainability · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersOcean Nexus Center, EarthLab, University of WashingtonHORIZON EUROPE Framework ProgrammeAustralian Research CouncilEuropean Commission
KeywordsTop-down and bottom-up designEcosystemEnvironmental resource managementBusinessEnvironmental planningGeographyEnvironmental scienceComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

Traditional approaches to maritime security focus on state and economic perspectives. We suggest that a more holistic approach to maritime security is needed that encompasses state, economic, human and environmental security to make maritime security more equitable, sustainable and responsive to contemporary social and environmental challenges. Adopting a normative human and eco-centric approach to maritime security, which revolves around the needs of coastal communities and the imperative of ocean sustainability, can be guided by four principles: participation and pluralism, autonomy and agency, equity and justice, and coherence and coordination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0080.079
Scholarly communication0.0170.020
Open science0.0020.015
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.014
GPT teacher head0.269
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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