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Record W4285005855 · doi:10.1016/j.isci.2022.104735

Development and expansion in the marine social sciences: Insights from the global community

2022· article· en· W4285005855 on OpenAlex
Emma McKinley, Rachel Kelly, Mary Mackay, Rebecca Shellock, Christopher Cvitanovic, Ingrid van Putten

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsStakeholderCorporate governanceStakeholder engagementMarine researchLiteracyPolitical scienceSociologyEnvironmental resource managementSocial sciencePublic relationsBusinessEnvironmental scienceOceanography

Abstract

fetched live from OpenAlex

The importance of understanding the complexities of societal relationships with our global ocean, and how these influence sustainable management and effective, equitable governance, is crucial to addressing ocean challenges. Using established horizon scanning method, this paper explores current trends in marine social sciences through a survey of the global marine social science research and practitioner community (n = 106). We find that marine social sciences research is broad, covering themes relating to governance and decision-making, stakeholder participation and engagement, the socio-cultural dimensions of marine systems, ocean literacy, community-based and area-specific management, and the blue economy, and identify future research priorities highlighted by the community. Our results, however, suggest several barriers persist, including the relationship between marine social sciences and other disciplines, and the visibility and recognition of marine social sciences both internal and external to academia. Finally, the paper generates prospective thinking and highlights recommendations for future research and practice.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.249
Teacher spread0.210 · 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