Language laws and education in Quebec: a case study of historic English- speaking parents' school choices in Notre-Dame-de-Grâce
Bibliographic record
Abstract
This thesis investigates how Quebec' s language legislation—particularly Bill 101 and Bill 96—shapes educational decisions among historically English- speaking parents in the Notre- Dame- de- Grâce(NDG) neighbourhood of Montreal. While prior research has predominantly focused on French- speakingor immigrant experiences, this study foregrounds a rarely examined group: English- speaking Quebecerswhose educational rights are constitutionally protected. Drawing on the policy feedback framework, pathdependency, and literature on sub- national identity, the study employs a qualitative research design basedon 15 semi- structured interviews with parents eligible under Bill 86. This eligibility refers to a parent whohas received elementary or secondary education in English in Canada, which grants their children the legalright to attend English public schools in Quebec. The findings reveal that language laws exert significantbehavioral influence, with most parents enrolling their children in bilingual or immersion programs to adaptto Quebec' s French- speaking- centered policy landscape. However, the policy' s effect on attitudes is moreambivalent: while bilingualism is widely valued, support for legislation such as Bill 96 is limited. The thesisalso identifies socioeconomic stratification, as wealthier families leverage private schooling to circumventpolicy constraints, while lower- income families experience reduced educational autonomy. Moreover,concerns about intergenerational eligibility and legal precarity contribute to anticipatory compliance,influencing school choice not only for the present generation but also for future ones. Some respondentseven considered relocation in response to perceived exclusion. Ultimately, this study highlights howlanguage policies operate not only as instruments of cultural preservation but also as mechanisms thatstructure identity, constrain mobility, and reproduce inequality. The case of NDG offers a microcosm ofbroader dynamics within Quebec' s multilingual society and raises questions about the sustainability ofcurrent policy models in promoting both inclusion and linguistic cohesion
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.
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 | 0.002 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".