Adult Migrants’ Formal and Informal Language Learning Opportunities: Availability, Choice, and Social Integration
Bibliographic record
Abstract
This study explores adult migrants’ formal and informal opportunities for learning their host country’s dominant language: specifically, the availability, accessibility, and effects of these opportunities on the migrants’ social integration. It prioritizes the migrants’ experience by reporting findings obtained from analyses of questionnaire data collected from 76 migrants in Canada, the United States, and Italy and from interview data collected from a subset of 18 of these migrants. The findings are supplemented by analyses of questionnaire data collected from 12 service providers at the same research sites. The findings show that across the three sites, adult migrants value both formal and informal learning opportunities; that in both learning contexts they prioritize the development of communicative competence, particularly speaking and listening skills; and that outside the classroom they prefer to interact with locals who do not share their home language, and find these interactions very useful in their social integration efforts. However, the findings also reveal that the migrants are not always able to choose freely to engage in the kinds of language learning opportunities that would help them meet their language learning or social integration goals because these opportunities may be unavailable, inaccessible, or insufficiently designed to meet their needs.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".