Il, elle, on…iel est : queer (socio) linguistics and identity amongst franco-anglophone gender non-binary young people in Montreal
Bibliographic record
Abstract
The city of Montreal is known for its linguistic diversity, with both French and English being dominant languages in specific spheres. Montreal has also long had a strong LGBTQ presence, which is a draw for many queer people moving to the city. However, for many non-binary people in the city, linguistic expression is a challenge, especially as grammatical gender in French makes expressing oneself as a gender other than male or female quite difficult. Using Queer Linguistics, poststructuralism, and Rymes’ (2014) concept of communicative repertoire as groundwork, this interview-based inquiry aims to create a better understanding of how young English-and-French speaking gender non-binary people living in Montreal navigate the French and English languages. This thesis explores how French grammatical gender has been adapted by these speakers. Factors found to be important were non-binary identities, changes in language use based on context, the social and linguistic spaces participants found to help foster self-understanding and inclusivity, and ways in which such spaces can be made more inclusive. Keywords: non-binary, transgender, grammatical gender, gender-neutral language, gender-inclusive language, Montreal, French, identity expression, poststructuralism, sociolinguistics, safer spaces
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".