Unilinguisme, bilinguisme et esthtique interculturelle dans les dramaturgies francophones du Canada
Bibliographic record
Abstract
In Canada, Francophone communities outside Quebec constitute a small minority in a mainly anglophone environment. In these communities, French is seen as an identity language by francophones who are bilingual out of necessity. The bilingualism of the Franco-Canadian communities, previously invested with the negative connotations specific to Quebec's perception of it, takes on a different added value within the context of globalisation. Furthermore, if it is seen as a corrupting influence on French within a context where French is the vehicular language, bilingualism becomes an instrument of resistance in a predominantly English context where it constitutes a condition sine qua non for remaining francophone. The resulting heterolingualism of Franco-Canadian drama seems to be increasingly accentuated as one moves westward from Ontario. On display in certain productions such as Roger Auger's Je m'en vais Rgina, Kenneth Brown's Cow-boy potr and Marc Prescott's Sex, Lies et les Franco-Manitobains, this heterolingualism represents a linguistic specificity within Canada's French-language drama repertoires. In order to reach a larger audience, certain plays have recently been presented with English surtitles that enable an exploration of new intercultural aesthetics inspired by the realities of life for Francophones within a minority context.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".