The role of archives in Indigenous language maintenance and resurgence
Bibliographic record
Abstract
For centuries, Indigenous peoples have been advocating for their rights to their land, cultures and languages in the context of (settler) colonial institutions that have repressed and removed these rights and knowledges, as well as the mechanisms for their transmission. This thesis attempts to open up questions regarding what settler-colonial archives and archivists could do to support Indigenous language maintenance, resurgence and use, given the reality that most Indigenous languages in Canada (and globally) are declining in use and number of speakers. Using Inuktut (Inuit languages) as a case study, it will outline the circumstances that have led to both this decline and the role that settler-colonial archives have had in it. By examining Inuktut records held by the settler-colonial institution of Hudson’s Bay Company Archives (HBCA) and their Names and Knowledge Initiative as a case study, this thesis will illustrate both the challenges posed by Indigenous language records held by such institutions, as well as the opportunities for (settler) colonial archives to contribute to Indigenous sovereignty over their linguistic data, knowledge and records. It will also explore the use of Indigenous languages in the delivery of services by archives to further support their use as languages of daily life.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.028 | 0.029 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".