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Human Use in World Heritage Natural Sites: A Global Inventory

2001· article· en· W2020122073 on OpenAlexaboutno aff
Jim Thorsell, Todd Sigaty

Bibliographic record

VenueTourism Recreation Research · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsWorld heritageIUCN Red ListNatural heritageGeographyTourismNatural (archaeology)Environmental protectionSocioeconomicsArchaeologyEnvironmental resource managementEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

As part of an on-going process of conducting global reviews of World Heritage (WH) natural sites and issues affecting them, IUCN conducted a study of human uses of all 129 natural and mixed natural sites on the WH List. In this overview, IUCN compiled the tourism data on each site to demonstrate just how substantial visitation numbers are and to detect variations between the different sites and continents. The global overview results are provided in this article, but some main conclusions on tourism are: Nearly 63 million people each year visit 118 World Heritage natural sites; 15 sites record over one million visitors/year with the Great Smoky Mts. Having the highest number (9,265,667); The 32 sites in USA, Canada, Australia and New Zealand accommodate over 84% all the visitors; The average visitation for the 30 sites in Africa is 22,705/year compared to 2.6 million visitors/year average in the 16 sites in USA and Canada; Economic valuations are available for some sites with the highest impact recorded for Yosemite ($1.3 billion/year) and a trend in all sites towards an increase in levels of visitation.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.308
GPT teacher head0.345
Teacher spread0.037 · 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 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

Citations25
Published2001
Admission routes1
Has abstractyes

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