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Record W4415593599 · doi:10.24043/001c.146163

Islandness of Sveti Stefan: A Collection of Particular Manifestations Through Time

2025· article· en· W4415593599 on OpenAlexvenueno aff
Goran Koprivica

Bibliographic record

VenueIsland Studies Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishSettlement (finance)DocumentationFoundation (evidence)Genius

Abstract

fetched live from OpenAlex

Sveti Stefan, a tiny Montenegrin island with a rich historical and cultural background, remains underexplored in academic research. Considering its physicality (shaped by nature and human intervention), circumstances that determined and directed its development (its settlement foundation from a seized Turkish treasure, its role as a small capital for surrounding villages, its gradual abandonment, its radical transformation into a luxury hotel), and its social structure (the original islanders later replaced by seasonal tourists), the paper investigates the islandness of Sveti Stefan, acknowledging both its literal and metaphorical meanings. Through a case study and literature analysis, combining theorization on islands and islandness with documentation on Sveti Stefan, this research explores the change of islandness of a particular place over time, as well as the contradictory nature of different manifestations of islandness, depending on external circumstances. The differentiation between general islandness and particular islandness—the former is seen as a shared potential among islands, the latter as a time-bound collection of qualities specific to each island—tends to reconcile the opposing sides of islandness manifestations and justify their coexistence. Susceptible to further change and redefinition, the islandness of Sveti Stefan represents a collection of every particular islandness that has manifested through time as an accomplished expression of general islandness.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.662
Threshold uncertainty score0.778

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 studies0.0010.000
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 head0.030
GPT teacher head0.354
Teacher spread0.324 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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