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Record W4392622172 · doi:10.24043/001c.94616

Regionalizing the Sustainable Development Goals for Island Societies: Lessons From Iceland and Newfoundland

2024· article· en· W4392622172 on OpenAlexaffvenueabout
Mark C. J. Stoddart, Ásthildur Elva Bernhardsdóttir, Yixi Yang

Bibliographic record

VenueIsland Studies Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEnvironmental planningGeographySustainable developmentRegional scienceEnvironmental resource managementPolitical scienceEnvironmental science

Abstract

fetched live from OpenAlex

The UN Sustainable Development Goals (SDGs) provide a framework that makes the concept of “sustainable development” more actionable. The nature of island societies — where political jurisdictions overlap in complex ways with land and oceanic ecologies — makes the question of who is responsible for SDG implementation and governance particularly important. We compare SDG interpretations and perceptions of SDG governance in Iceland and Newfoundland using survey and focus group data with stakeholders from government, business, labour, civil society, academia, and youth. Our research questions are as follows: How do research participants view the SDGs in relation to ensuring sustainable futures for their respective island societies? How do research participants view the roles of government and other institutions in implementing sustainability? Answering these questions gives insight into a third theoretically valuable question: Is it the state versus subnational jurisdiction distinction, or is it the common small polity/island dynamics of these cases that is important for understanding the interpretations of the SDGs and their implementation? The interpretations of regionalizing and localizing the SDGs are similar across our two cases, which lends support to a small polity/islandness view of how the SDGs are translated for island societies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.072
GPT teacher head0.391
Teacher spread0.320 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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