Bibliographic record
Abstract
"Incendies" is a 2011 Canadian film produced by the director Denis Villeneuve. After their mother's death, the twins Jeanne and Simon are placed by her - for her speech, for her language that still echoes - in certain positions. They are demanded to assume certain positions in relation to the Other. We take this work as a starting point to develop some reflections about the mother language - a relatively unstable and polysemic notion/concept. Writing from an interlocution between French Discourse Analysis and Psychoanalysis, we seek to answer the following provocation: How does the mother language cross the subjects and collaborate in the construction of subjectivities? More than a research problem, this is a concern that presents itself to us. To answer this question, we have as a general objective to discuss the concept - or notion - of mother language from « Incendies ». As a specific objective, we seek to analyze a possible approximation between mother language and speech - within this filmic work. Based on the literature consulted for the development of this text, we were able to consider at the end of its writing, that the mother tongue affects the subject in an extremely potent way, in a way that other languages do not necessarily do, since this language called mother language, due to the proximity to the mother, brings marks of this singular relationship that never fail to affect the subject. Keywords: Mother language; Cinema; Speech; Psychoanalysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 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".