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Record W4361197046 · doi:10.1080/08941920.2023.2185844

Measuring Tourism Impacts on Community Well-being at the Hani Rice Terraces GIAHS Site, Yunnan Province of China

2023· article· en· W4361197046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociety & Natural Resources · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Systems and Practices
Canadian institutionsUniversity of Waterloo
FundersMinistry of EnvironmentNational Natural Science Foundation of China
KeywordsTourismChinaGeographyStakeholderAgricultureLocal communityEnvironmental planningEnvironmental resource managementRegional sciencePolitical science

Abstract

fetched live from OpenAlex

To reflect the intricate relationships between heritage, tourism, and community pertinent to Globally Important Agricultural Heritage Systems (GIAHS), the framework of community well-being is adapted to evaluate the status and changes to destination communities imposed by conservation and tourism initiatives. A multi-stakeholder, mixed-method approach is adopted using qualitative interviews and a quantitative questionnaire survey at two villages of the Hani Rice Terraces, Yunnan Province of Western China. Results show that positive impacts from tourism are mainly concentrated on the environmental, conservation, and development dimensions. However, the lack of improvements in the education and health dimensions negatively affected the well-being of the local community. In particular, the subjective well-being is reduced with the increasing need for education induced by tourism. The evolution of community well-being is explored and portrayed through well-being hexagons and measures to enhance the positive impacts of tourism are proposed for GIAHS and other heritage sites or protected areas.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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