Auto-histoires et représentations communautaires dans le cinéma des femmes autochtones
Bibliographic record
Abstract
In the last decade or so, cinema has revealed itself to be an ideal medium for the transfer and/or remediation of the spoken word as well as stories coming from oral tradition and Indigenous culture. Indeed, cinema is a place of expression which favours cyclical creativity and contributes to the decolonization of stereotyped images propagated by external voices that do not understand the subtleties of languages (real and symbolic) that are anchored in indigenous peoples’ cultural memory. By exploring indigenous cinema as practised by women of diverse nations, this piece demonstrates how cinema can induce the compression and dilation of time, to bring to the audience the fluidity of a story that has been reconfigured according to a new time and carried by spoken words that have chosen to either emancipate themselves from the image or to materialize themselves in it. Furthermore, this article illustrates how a new generation of Indigenous women use cinema to retrace and/or rewrite their personal narrative with the help of autobiographical or collective stories that travel back in time to fill in the blanks left by a fragile memory and to express their will to make peace with a difficult colonial past. Finally, the writings of Lee Maracle ( I Am Woman, 1988) and Natasha Kanapé Fontaine ( Manifeste Assi, 2014) are being brought forth to show how films such as Suckerfish (Lisa Jackson, 2004) Bithos (Elle-Máijá Tailfeathers, 2015) and Four Faces of the Moon (Amanda Strong, 2016) contribute to the individual and community healing of Indigenous peoples of Canada, through an aesthetic of reconciliation. The exploration of these works, therefore allows us to shed light on and better understand the roles/internal mechanisms of visual autobiographies in the larger context of reconciliation with individual and collective stories/memories.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".