Chasing Canadian dreams through learning French: A narrative study on new Chinese immigrants’ transnational and learning experiences in Montreal
Bibliographic record
Abstract
This research examines the French learning experience of Chinese new immigrants who landed and lived in Quebec within 5 years. Limited research focused on the lived experience of Chinese immigrants and their French learning paths, although they were the second largest group of immigrants in Quebec from 2019 to 2023. Due to the unique history and official language requirement of Quebec, the Ministère de l’Immigration, de la Francisation et de l’Intégration (MIFI) funded new immigrants to learn French to accelerate their integration in Quebec. However, this monolingual teaching courses did not fully prepare them to fulfill their language and employment aspirations. Thus, the research question arises as to (1) how the government-funded francization program shapes and supports new Chinese immigrants’ realization of their Canadian dreams; and (2) how the Chinese new immigrants agentically makes sense of their new life in Quebec and actively pursues their aspirations through attending the MIFI programs? Informed by the theoretical frameworks of transnationalism, assimilationism, and cultural citizenship, the study employs narrative inquiry as its methodology to explore the lived and learning experience of new Chinese immigrants. The author recruited 5 participants to investigate their life history as they traveled between Canada and China, pursued initial Canadian dreams and aspirations, learned in MIFI, and formulated their evolving identities. From the transcription of semi-structured interviews in the summer of 2024, I argue that three aspects should be taken into consideration to help new immigrants reach their aspirations: the one-size-fit-all monolingual teaching method doesn’t consider the diverse background of students, the sexual harassment happened in schools lacks the monitor and reporting systems, the barriers in employment such as professionalism and social network could be addressed in courses and activities.The study helps to bridge the research gap in the Chinese community in Quebec after the Covid-19 pandemic. It furthers the understanding of their French learning paths and lived experience under Bill 96. During the writing process, the study records timely social changes in immigrant policy and the special phenomenon of Chinese peidu mothers’ dilemma (who accompany their children to study abroad while their partners are working back in China), which have influenced participants’ future plans and provided further research directions in this ethnic community
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".