Visual convincing of intangible cultural relationships using maps: A case study of the Tongariro National Park World Heritage nomination dossier
Bibliographic record
Abstract
UNESCO World Heritage site nominations require the use and presence of maps and GIS to demarcate potential heritage property boundaries. UNESCO and the World Heritage Committee provided specific cartographic guidelines and standards for the inclusion of maps within the nominations. The New Zealand government used maps and GIS to visually convince UNESCO, the World Heritage Committee, the International Union on the Conservation of Nature, and the International Council on Monuments and Sites of intangible cultural relationships at Tongariro National Park. More specifically, New Zealand combined scientific maps, Māori language narratives, and symbols to make the intangible tangible and geographically visible. Maps and GIS images that accompanied World Heritage nomination dossiers were housed at the UNESCO World Heritage Centre and the International Council on Monuments and Sites in Paris, France. The first section of the paper introduces the data sources and methods used in our archival research. Next, we provide a brief description of the Tongariro National Park nomination and present a case study on, and interpretation of, the maps and GIS contained within the Tongariro National Park World Heritage nomination dossier. Finally, we will offer some conclusions and directions for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".