Indigenous data sovereignty in intangible cultural heritage governance: A complementary approach to public–private partnerships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article examines the challenges Indigenous communities face in safeguarding their intangible cultural heritage (ICH) in the digital age, using two case studies. Referring to the Te Hiku Media case, it analyzes the threat of data colonialism posed by corporate digitization projects. The article argues that existing legal frameworks provide limited protection for Indigenous ICH, prompting Indigenous communities to develop the innovative theory of Indigenous data sovereignty (ID-SOV). The Government of Nunavut–Microsoft partnership case highlights the benefits and drawbacks of public–private partnerships (PPPs) for Indigenous ICH. Key takeaways from both cases’ analysis lead to our proposal of integrating ID-SOV principles into PPPs to limit data colonialism risks and improve the sustainability of Indigenous ICH digitization projects. The article contends that implementing ID-SOV principles by design and by default in PPPs can empower Indigenous communities while leveraging the oversight of public actors and resources of private partners to safeguard Indigenous ICH through digital tools.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it