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Record W4409380110 · doi:10.1007/s40152-025-00423-2

Privatisation from a coastal community perspective

2025· article· en· W4409380110 on OpenAlexafffund
Anthony Charles

Bibliographic record

VenueMAST. Maritime studies/Maritime studies · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsSaint Mary's University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPerspective (graphical)Environmental planningOceanographyEnvironmental resource managementGeographyEnvironmental scienceGeologyComputer science

Abstract

fetched live from OpenAlex

This article explores processes and impacts of privatisation from the perspective of coastal communities, drawing on ideas of governance, rights and the Commons, as well as previous studies of privatisation and the associated phenomenon of ‘grabbing’. The analysis shows how diverse mechanisms of privatisation are reflected in five key dimensions, relating to (a) jurisdictions; (b) the range of rights; (c) magnitude of privatisation; (d) distributional implications; and (e) community perceptions. The practical aspects of these privatisation dimensions are illustrated through three coastal community examples, drawing on several years of participatory research, with various qualitative methods producing a set of insights from community participants. A key result relates to how the community perceives privatisation, which depends less on the generic attributes of privatisation and more on how well the outcomes fit with the community’s underlying values and strategic goals. Accordingly, among the many complexities of privatisation, attention to community perceptions may be especially important, particularly in terms of community reactions to privatisation of different forms. This fits with governance results from elsewhere, and reinforces the need to understand community aspects of the Commons, with implications for the ‘blue economy’ and the future of a possibly privatized ocean.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.018
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.300
Teacher spread0.272 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2025
Admission routes2
Has abstractyes

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