Bibliographic record
Abstract
This article draws on participant observation in a legal battle at the Quebec Superior Court in 2022, where the Kanien’kehá:ka Kahnistensera (Mohawk Mothers) sought an injunction to halt excavation work around a hospital where Indigenous victims of medical experiments were allegedly buried. In response to a motion from the government of Quebec, the Mohawk Mothers refused to use a lawyer who would obey colonial law, arguing that it was their traditional duty as caretakers of the territory to speak for themselves and for their community without legal representation. This article examines their fight for self-determination through their specific understanding of the relationship between individual autonomy and social responsibility, notably by way of the Kanien’kehá:ka’s use of a single word to denote assemblies, fires, and families: Kahwá:tsire’. To reach a consensus, when it seems that everyone has come to an agreement, the Kanien’kehá:ka council must “stir the ashes” and ask everyone who has not spoken yet to voice their opinion and bring their unique perspective in the balance. As a result of this method, the author suggests that the Kanien’kehá:ka simultaneously take on the roles of legislators, executors, and judges all at once.
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.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.037 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".