Expectations versus reality: Maghrébine women's lived experiences of language policy in Montreal
Bibliographic record
Abstract
Quebec is a unique place where language is highly politicized (Bourhis, 1984; Levine, 1990; Corbeil, 2007; Oakes & Warren, 2007). Issues of language intersect with all aspects of immigration and integration. I consider policies to be "virtual realities" (Moore, 2000) that must be understood in conjunction with their interaction with ideologies and practices (Spolsky, 2004). This study responds to the call to undertake language policy research that emphasizes individual experiences and brings language policy from a bureaucratic field to a human one (Shohamy, 2009). The overall objective of this study was to question how the expected outcomes of Quebec government policies compare with the lived experiences of three recently immigrated North African women. More specifically, the resulting critical ethnography examines existing and proposed government policies (such as the Charter of the French Language, Quebec and Canadian immigration policy, Quebec interculturalism, and the Charter of Values), in conjunction with interviews and journal data collected from three women working in the public education sector in Montreal. The findings show that the real world experiences of individuals often do not correspond with the intended outcome of the policies that govern them. Furthermore, the results show that categorizations of language (e.g. allophone, francophone) are often used as a site of differentiation (Haque, 2012); there is a contradiction between policies' conceptualization of French in Quebec as a unifying common public language, and perpetuation of French belonging to the French Canadian ethnic group. This study ultimately advocates for further rapprochement within Quebec society, and an inclusive vision of language and identity.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".