Indigenous Peoples, Data Sovereignty and Self-Determination: Current Realities and Imperatives
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
This study explores the current state and dynamics of the global Indigenous data sovereignty movement-the movement pressing for Indigenous peoples to have full control over the collection and governance of data relating to their lived realities. The article outlines the movement's place within the broader push for Indigenous self-determination; examines its links to big data, open data, intellectual property rights, and access and benefit-sharing; details a pioneering assertion of data sovereignty by Canada's First Nations; outlines relevant UN and international civil society processes; and examines the nascent movement in Africa. The study identifies a fundamental tension between the objectives of Indigenous data sovereignty and those of the open data movement, which does not directly cater for Indigenous peoples' full control over their data. The study also identifies the need for African Indigenous peoples to become more fully integrated into the global Indigenous data sovereignty movement.
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 | 0.002 | 0.027 |
| Open science | 0.002 | 0.002 |
| 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 it