Images de résistance : le cinéma autochtone au Québec et la lutte contre l'érosion culturelle
Bibliographic record
Abstract
This thesis is situated within the fields of film studies, cultural studies, and Indigenous studies. It explores the role of Indigenous cinema in Quebec in the fight against cultural erosion. The focus is on how Indigenous peoples use cinema to assert their right to memory and to preserve their cultures, demonstrating resilience while reconstructing their collective identity. The study is organized around three key axes: the documentation of Indigenous history through film, the transmission of cultural and linguistic heritage via cinematic works, and the impact of these films as catalysts for intercultural dialogue and social change.The works of filmmakers such as Alanis Obomsawin, Kim O’Bomsawin, Jeff Barnaby, Skawennati, and Tracey Deer are analyzed to illustrate how their films serve as vehicles for resistance, identity assertion, and platforms for intercultural dialogue. Both documentary and fiction cinema are highlighted as powerful tools for cultural preservation and revitalization, functioning as living archives that allow for an ongoing re-evaluation of the past and strengthen collective memory.This thesis emphasizes the importance of Indigenous cinema in the reaffirmation of cultural sovereignty and the critique of colonial perspectives, while offering authentic and diverse representations of Indigenous experiences.In conclusion, Indigenous cinema in Quebec emerges as a vital force for the preservation, reclamation, and celebration of the culture and history of Indigenous peoples, contributing to the resilience and vitality of Indigenous communities while fostering enriched and inclusive intercultural dialogue.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".