Becoming Citizens: Racialized Conceptions of ESL Learners and the Canadian Language Benchmarks
Bibliographic record
Abstract
In this article, I report a qualitative study that sheds light on how adult learners of English as a Second Language (ESL) are constructing new national identities in the context of the challenges associated with immigration. In particular, I trace how the common threads among their conceptions of citizenship compare with those embedded within official, national assessment, and curriculum documents. Using a broad questionnaire and a focused set of semi‐structured interviews at a large ESL site in British Columbia, my research reveals the gaps between the experiences of these immigrants and how these documents construct and position idealized and racialized conceptions of second language learners. Key words: Adult ESL; identity; immigration; assessment and curriculum documents; semi‐structured interviews; gap analysis; racialized conceptions; language learning; Lang‐ uage Instruction to Newcomers to Canada (LINC); language policy and planning Dans cet article, l’auteur présente une étude de cas qualitative qui permet de mieux com‐ prendre comment des adultes apprenant l’anglais à titre de langue seconde (ALS) se façon‐ nent de nouvelles identités nationales dans le cadre des défis associés à l’immigration. L’auteur analyse tout particulièrement de quelle manière les éléments communs de leurs conceptions de la citoyenneté se comparent à certains des thèmes des documents de curri‐ culum et d’évaluation officiels. Reposant sur un vaste questionnaire et une série ciblée d’entrevues semi‐structurées menées dans un grand centre d’ALS en Colombie‐ Britannique, cette recherche révèle les écarts entre les expériences de ces immigrants et la façon dont ces documents créent et positionnent des conceptions à la fois idéalisées et racia‐ lisées des personnes apprenant une langue seconde. Mots clés : adultes en ALS, identité, immigration, documents d’évaluation et de curricu‐ lum, entrevues semi‐structurées, analyse des écarts, conceptions racialisées, apprentissage d’une langue, Cours de langue pour les immigrants au Canada (CLIC), politique ‐et amén‐ agement linquistiques
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.026 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| 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".