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Record W2944496467 · doi:10.24043/isj.86

Sense of place predictors of perceived effects of a proposed island to mainland bridge on future experience

2019· article· en· W2944496467 on OpenAlexaffvenue
Jana Raadik, Stuart Cottrell

Bibliographic record

VenueIsland Studies Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsBridge (graph theory)MainlandSense of placeMainland ChinaGeographyForensic engineeringHistoryEconomic geographyPsychologyAestheticsEngineeringArchaeologyArtMedicineChina

Abstract

fetched live from OpenAlex

This paper examines how Estonian and foreign tourists to Saaremaa Island perceive their future experiences in light of a bridge built from mainland Estonia to the island. A logistic regression resulted in six predictors (two demographic and four sense of place scales) of perceived future effects of a proposed bridge on future experience, accounting for 18% of the variance. The six predictors of perceived effects of a potential bridge to the mainland on future holiday experience to Saaremaa Island were nationality, education, socio-cultural context, memory, aesthetics, and wellbeing sense of place scales. Estonians were more positive about the bridge, which supports previous discussions of the essence of home and wellbeing. Wellbeing was the strongest and only positive predictor followed by educational level, memory, socio-cultural context, aesthetics, and nationality, which were all negative. Highlights allude to the predictive power of sense of place on perceived environmental change of development (bridge to island) to future experience among tourists.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.297
Teacher spread0.286 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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