Hétérogénéité et pensée frontalière dans la littérature amérindienne
Bibliographic record
Abstract
Cet article montre comment certaines théories provenant de l’Amérique latine peuvent être utilisées pour analyser la littérature amérindienne au Québec. L’auteur présente d’abord le concept d’hétérogénéité tel que développé par le critique littéraire péruvien Antonio Cornejo Polar, qui prétend que la réalité socioculturelle des sociétés américaines peut se concevoir comme un « tout » dans lequel s’opèrent divers niveaux de tensions et de conflits dérivant de l’expérience coloniale, et sa convergence avec certaines des propositions des études coloniales et « décoloniales » latino-américaines. Par la suite, ces théories sont appliquées au champ littéraire amérindien du Québec et montrent comment l’hétérogénéité manifeste une pensée frontalière décolonisatrice dans la littérature actuelle à travers divers dispositifs comme lagnosis frontalière, lapensée autreet lalangue autre. Le propos de l’auteur est illustré par une analyse de l’autobiographie d’An Antane KapeshJe suis une maudite sauvagesseet du recueil de poésieBâtons à messagede Joséphine Bacon.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".