Decolonizing World Heritage Maps Using Indigenous Toponyms, Stories, and Interpretive Attributes
Bibliographic record
Abstract
Maps and GIS used for the nomination and subsequent management of UNESCO World Heritage sites have primarily served bureaucratic resource management purposes. However, bureaucratic maps offer an opportunity to represent associative cultural landscapes, intangible cultural elements, and the geographies of Indigenous peoples. Indigenous toponyms can be found on many World Heritage maps for sites located within settler societies such as New Zealand, Australia, the United States, and Canada. Currently, bureaucratic heritage maps do not emphasize or even have a method for presenting the meaning and significance of Indigenous toponyms. Instead, the names are represented as static, inanimate objects void of meaning. This article presents archival evidence that bureaucratic state maps found within some UNESCO World Heritage nomination dossiers and resource management plans contain Indigenous cartographic elements that Indigenous communities could use as the basis for creating Indigital story maps.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".