Language Hierarchies, Liminality, and Resistance in Canadian and Finnish Integration Educations for Adult Migrants
Bibliographic record
Abstract
This article explores the effects of language hierarchies within SFI (Swedish for Immigrants) and LINC (Language Instruction for Newcomers to Canada) national integration programmes and how discourses of civic integrationism framed around monolingualism and neoliberalism position adult migrant students in the liminal spaces between belonging and othering. Based on research findings obtained during multiple case study fieldwork in Finland and Canada, I examine the underlying norms and subtexts upon which practices of host language acquisition are founded. How students are positioned depends greatly on who serves as an arbiter over which expressions of linguistic diversity are deemed beneficial or obstructive to integration. Migrant liminality within integration educations could be debilitating while simultaneously fostering resistance in transgressing and reimagining essentialist integration policy and pedagogical goals, thus creating opportunities for transformation.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.014 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 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".