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Record W2516558883 · doi:10.3390/su8090886

How to Promote Sustainable Relationships between Heritage Conservation and Community, Based on a Survey

2016· article· en· W2516558883 on OpenAlexaff
Fang Han, Zhaoping Yang, Hui Shi, Qun Liu, Geoffrey Wall

Bibliographic record

VenueSustainability · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Waterloo
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsCultural heritageCultural heritage managementIndustrial heritageEnvironmental resource managementCitizen journalismEnvironmental planningSustainable developmentNatural heritageLocal communityNatural resource managementCommunity managementNatural resourcePolitical scienceValuesGeographyManagementArchaeologyTourismEconomics

Abstract

fetched live from OpenAlex

Community residents have a strong stake in a local heritage site and may be an important force in its conservation, management and development. Positive relationships between the heritage site and community residents can promote its protection. A questionnaire survey was conducted with local residents of Bogda World Natural Heritage, Xinjiang, China, to assess their perceptions towards the World Natural Heritage, and their attitudes towards participation in heritage conservation. The local residents have made positive contributions to the conservation of heritage resource in the past several years. However, because of the asymmetry between responsibility for conservation and benefit sharing, the authors recommend that a “Community co-management framework” should be established to mobilize residents to participate in heritage conservation. Furthermore, participatory approaches and communication mechanisms are suggested to promote sustainable relationships between community development and heritage conservation. The empirical study can be used as an input to policy making and management for sustainable conservation, and the study contributes to the literature related to community participation at heritage sites.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.295
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.146
GPT teacher head0.271
Teacher spread0.125 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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