Heritage Language Maintenance: The Case of Bangladeshi Immigrants in Canada.
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
Immigrant parents not only face assimilation challenges in a new country, but many also find it difficult to connect their children with their heritage culture. As language plays an important in conveying and practicing culture, the challenges associated with preserving heritage language in immigrant families have not received much attention in the literature. In this paper, we focus on the Bangladeshi community in Canada and interview 20 Bangladeshi immigrant parents to explore the various concerns they have regarding preserving their heritage language and discuss two different approaches to learning through the presentation of language acquisition applications. Based on our study, we report the cultural tensions, economic constraints, and infrastructural challenges the immigrant families face while teaching heritage languages to their children. We also provide a set of design implications to better facilitate heritage language maintenance and associate our findings with some broader concerns in the HCI literature around migration, memory, identity, and learning.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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