Critical Social Inclusion of Adult Migrant Language Learners in Working Life: Experiences From SFI and LINC Programs
Bibliographic record
Abstract
How can integration education programs facilitate the more seamless inclusion of migrant newcomers into working life and civil society? Traditionally, integration policy and practice have been framed within a nation‐state discourse in which views of migrant incorporation are grounded within a bordered nationalism embodying a native–migrant dichotomy that reifies the view of the “migrant other” as a subject defined by its “lack” in competence and agency. In our qualitative multiple case study, we explored the bridging potential of integration programs in facilitating the inclusion of migrant students within working life in Helsinki and Edmonton. We examined the “inclusectionalities,” referring to the intersections of inclusion and exclusion that position adults enrolled in SFI (Swedish for Immigrants) and LINC (Language Instruction for Newcomers to Canada) language integration programs in the liminal spaces between belonging and othering. Guided by an understanding of critical social inclusion where migrants set the boundaries for interactions with authorities based upon their own needs and interests, we propose a transformational approach. Here migrant learners participate in a structural process where the fluid nature of social, political, and economic arrangements is consistently renegotiated on principles of egalitarianism and the full exercise of critical agency, herein envisioned as deliberate action resisting the social domination of racialized minorities by challenging and redefining institutional structures.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.020 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.004 | 0.006 |
| 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".