<i>Lingua Nullius</i>: Indigenous Language Learning and Revitalization as Sites for Settler-Colonial Violence
Bibliographic record
Abstract
This article examines the role that Indigenous language learning and use can play in the establishment of false or spurious claims to Indigeneity. These acts of “race shifting” are situated within the political discourse of “Truth and Reconciliation” and serve to enable settlers to situate themselves in positions where, both materially and symbolically, they rely on their claims to “Indigeneity” to take up resources dedicated to Indigenous people. Indigenous language use and language revitalization programs provide tools that can enable these performances of Indigenous identity to become more widely accepted among predominantly settler audiences. We argue that increasing consciousness of the inherently political nature of Indigenous language work – often framed as a move toward language reclamation – must be pushed even further, to consider the possibility that some users are not reclaiming but in fact claiming. These acts of claiming the language function in much the same way as claims to land have within settler colonialism – to dispossess Indigenous people and to disrupt Indigenous sovereignty.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".