Indigenous sovereignty in digital territory: a qualitative study on land-based relations with #NativeTwitter
Bibliographic record
Abstract
Technology scholars have often framed cyberspace as landless. Critical technology and Indigenous new media scholars have critiqued this approach, citing the land-based nature of Internet infrastructure. This study seeks to further develop the conceptual framework of Indigenous land-based relations through qualitative analysis of Indigenous language revitalization networks within Twitter. Using a thematic analysis approach, six key themes emerged: (a) Land-based cyber-pedagogy, (b) Rematriations of land-based relations in digital environments, (c) Digital bridges to homelands and lifeways, (d) Networked cultural navigation, (e) Settler colonialism in cyberspace, and (f) Indigenous digital sovereignty and cyber-justice. Implications for theory and practice in both new media studies and language revitalization are considered, with a focus on elucidating the land-based nature of the Internet, Indigenous people's navigation of colonialism within the Internet, and the meaning of anti-colonial resistance in cyberspace.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 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; a candidate call from one teacher head, 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".