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A Cultural Perspective on Wildlife Tourism in China

2012· article· en· W2079589166 on OpenAlexaff
Qingming Cui, Honggang Xu, Geoffrey Wall

Bibliographic record

VenueTourism Recreation Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
FundersNational Science Foundation
KeywordsWildlife tourismWildlifeTourismChinaHarmony (color)Wildlife conservationNorth American Model of Wildlife ConservationPerspective (graphical)Wildlife managementTourism geographyEcotourismGeographyEnvironmental resource managementCultural valuesEnvironmental ethicsEnvironmental planningSociologyEcologySocial science

Abstract

fetched live from OpenAlex

Wildlife tourism is based on interactions between humans and wildlife. Although it is well understood that differences exist in the relationship in different cultures, existing management models are often based on a scientific approach rather than a cultural approach or an approach that integrates these perspectives. This study concentrates on the social and cultural factors affecting wildlife tourism management through a case study of Monkey Island in Hainan Province, China. Various stakeholders were interviewed about their views on conservation and tourism management. The “differential mode of association” of Chinese culture is used to understand conflicts and harmony in nature conservation and tourism development. It is shown that Chinese people are accustomed to treat wildlife in aesthetic and moral ways. A conservation model that does not take account of these cultural factors is likely to be ineffective. The research establishes and demonstrates the need and potential to study wildlife tourism from a cultural approach.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.099
GPT teacher head0.461
Teacher spread0.362 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations34
Published2012
Admission routes1
Has abstractyes

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