Human Use in World Heritage Natural Sites: A Global Inventory
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".