Fee-Paying English Language Learners: Situating International Students’ Impact on British Columbia’s Public Schools
Bibliographic record
Abstract
This article examines the relationship between international education and English as an additional language (EAL) education in British Columbia’s public education system. Drawing on a wide range of data generated as part of a longitudinal study of high school aged fee-paying international students (FISs) in an urban school district in British Columbia, I make the case that FIS recruitment and presence is having a socializing impact on EAL education in British Columbia’s public schools. In contrast to the way FISs are accounted for in official government statistics, I show how, across multiple actors and dimensions of the public system, FISs are routinely treated and represented as English language learners (ELLs). I argue that these routinized constructions are evidence of the multilayered socialization of EAL education by internationalization efforts in British Columbia’s K-12 sector, and discuss some of the ways this FIS socialization is consequential for EAL learning and teaching in public high schools. I situate my discussion of the FIS-EAL relationship within the larger context of applied linguistics and education-related research on internationalization and educational migration in K-12 settings, and raise questions about how FIS socialization is relevant to discussions of public education.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".