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Record W2612521098 · doi:10.24043/isj.6

Sustainable local development on Aegean Islands: a meta-analysis of the literature –

2017· article· en· W2612521098 on OpenAlexaffvenue
Sofia Karampela, Charoula Papazoglou, Thanasis Kizos, Ιoannis Spilanis

Bibliographic record

VenueIsland Studies Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity and Sustainable Development
Canadian institutionsUniversity of Prince Edward Island
FundersUniversity of the AegeanEuropean Commission
KeywordsMeta-analysisGeographyMedicine

Abstract

fetched live from OpenAlex

Sustainable local development is central to debates on socioeconomic and environmental change. Although the meaning of sustainable local development is disputed, the concept is frequently applied to island cases. Studies have recently been made of many local development initiatives in different contexts, with various methods and results. These experiences can provide valuable input on planning, managing, and evaluating sustainable local development on islands. This paper provides a literature review of positive and negative examples of sustainable local development for the Aegean Islands, Greece. Out of an initial 1,562 papers, 80 papers made the final selection based on theme, empirical approach, and recency. The results demonstrate a wide thematic variety in research topics, with tourism, agriculture, and energy being the most frequent themes, while integrated frameworks are largely absent. The literature includes a wide range of methods, from quantitative approaches with indicators and indexes to qualitative assessments, which blurs overall assessments in many instances.

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)0.035
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.037
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.015
Bibliometrics0.0370.031
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.087
GPT teacher head0.365
Teacher spread0.278 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations31
Published2017
Admission routes2
Has abstractyes

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