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Record W1966327240 · doi:10.1080/15022250.2010.496570

Cultural Clash: Interpreting Established Use and New Tourism Activities in Protected Natural Areas

2010· article· en· W1966327240 on OpenAlexaboutno aff
Kerry Wray, Stephen Espiner, Harvey C. Perkins

Bibliographic record

VenueScandinavian Journal of Hospitality and Tourism · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsWildernessTourismRecreationWilderness areaTourism geographyNatural resourceNational parkNatural (archaeology)Resource (disambiguation)GeographyEcotourismPolitical scienceEnvironmental resource managementEnvironmental protectionArchaeologyEcology

Abstract

fetched live from OpenAlex

Abstract Protected natural areas are a significant tourism resource in many countries, including Norway, Sweden, Canada, Australia and New Zealand. The provision of tourism facilities in such areas is increasing but this is not without controversy. Tensions have arisen in some areas where international tourist visitation is believed to be affecting traditional cultural and recreational practices. Despite this, little research attention has been given to exploring local users’ attitudes towards tourism activities in areas where they have traditionally not existed. Using Fiordland National Park as a case study, this paper reports research on recreational wilderness use in New Zealand by locals and visiting international tourists. Its focus is on local recreationists’ attitudes towards international wilderness tourism. The discussion draws on data gathered using in‐depth interviews and research diaries. Findings revealed that international tourists were often viewed as a threat to New Zealanders’ recreation opportunities and cultural identity. These attitudes appear to be influenced by widely held values and beliefs about the purpose of public conservation lands. A consideration of the links between the natural environment and national identity is seen as crucial when planning for tourism in protected natural areas in the future.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.097
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.303
Teacher spread0.282 · 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 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

Citations41
Published2010
Admission routes1
Has abstractyes

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