Indigenous Literatures at the Crossroads of Languages: Approaches and Avenues
Bibliographic record
Abstract
This article examines critical discourses and approaches for the study of Indigenous literatures across languages. On the one hand, it investigates how the French-English divide is challenged by Indigenous authors and how it has been and can be further dealt with in Indigenous literary studies (ILS). On the other hand, it pays attention to the centrality and revitalization of Indigenous languages as they challenge colonial languages, complicate the French-English divide in ILS, and center Indigenous experiences. Engaging with the question “what approaches can scholars, teachers, and students in Indigenous literary studies use for the study of Indigenous literatures at the crossroads of languages?”, I highlight multilingual work by Indigenous authors, collect resources that directly engage Indigenous literatures from a (multi)language perspective, and gather approaches that can be helpful in developing a framework for the study of the multilingual corpus of Indigenous literatures.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.024 | 0.053 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".