Best Cultural Heritage Stewardship Practices by and for the White Mountain Apache Tribe
Bibliographic record
Abstract
As is true for most indigenous programmes concerned with cultural heritage management, the White Mountain Apache Tribe Historic Preservation Office (THPO) operates at dynamic and contested intersections of expanding populations and economies, shrinking budgets, diversifying international interests in heritage issues, and increasing indigenous demands for self-governance, self-reliance, self-determination, and self-representation. Faced with limited funds, large mandates, and land users having variable support for cultural heritage protection, the White Mountain Apache THPO has harnessed long-standing and emergent community heritage values as authentic foundations for 'actionable' rules promoting consultation, identification, documentation, and protection for tangible and intangible cultural heritage. Developed on the basis of a decade of interactions with elders and other cultural experts, foresters, hydrologists, engineers, and planners, the Tribe's Best Cultural Heritage Stewardship Practices illuminate challenges and opportunities faced by many THPOs and illustrate the crafting of appropriate institutional frameworks for community-based historic preservation initiatives.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".