Binary-constrained code-switching among non-binary French-English bilinguals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents data on non-binary French-English bilinguals’ metalinguistic analyses of their code-switching behavior in discussing their gender identities. Six non-binary French-English bilinguals were recruited for sociolinguistic interviews via Montréal-based LGBT+ organizations and asked about their experiences using non-binary French and English, especially how they describe themselves in each language. Participants’ preferences for using English to describe issues of gender identity reveals a particular type of topic-based code-switching is utilized in this community—a novel phenomenon that I have deemed Binary-Constrained Code-Switching, where participants switch out of an L1 (French) into an L2 (English) because they perceive their L1 as lacking the appropriate lexicon or grammatical features, specifically non-binary pronouns and gender agreement markers, to index their gender identities. In parallel to their dispreference for using French to describe their gender identities, participants’ preference for using English correlated with their perceptions of English as a more gender-neutral language than French, as well as a language with more linguistic resources—chiefly, vocabulary— to describe LGBT+ identities (c.f. queer). The data presented here not only supplement the primarily binary gender models found in extant studies of socially-motivated code-switching, but also provide greater evidence for the perceptual link between grammatical gender and social gender.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it