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Record W2145291418 · doi:10.1080/09669580802159685

Resident Attitudes Towards Mountain Second-Home Tourism Development in Norway: The Effects of Environmental Attitudes

2008· article· en· W2145291418 on OpenAlexaboutno aff
Bj⊘rn P. Kaltenborn, Oddgeir Andersen, Christian Nellemann, Tore Bjerke, Christer Thrane

Bibliographic record

VenueJournal of Sustainable Tourism · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTourismDependency (UML)PerceptionPlace attachmentEconomic growthSocioeconomicsGeographyPsychologySocial psychologySociologyEconomics

Abstract

fetched live from OpenAlex

Rural tourism, especially through second-home development is increasing rapidly in much of Europe, the USA and Canada offering new economic opportunities for local communities, but also challenges related to environmental impacts and differing perceptions within communities about appropriate development paths. This study examines associations between the environmental attitudes of residents and attitudes towards second-home development in two regions in Southern Norway, with community attachment and economic dependency as additional predictors. Ecocentrism was found to have a strong negative effect on attitudes towards tourism development, while, in contrast to previous findings, community attachment did not have significant effects. Economic dependency is significantly related to attitudes towards development; both ecocentrism and economic dependency are mediated by other variables, such as expected impacts and benefits. The findings are important in planning to reduce potential conflicts.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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 designObservational
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

Citations128
Published2008
Admission routes1
Has abstractyes

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