Bibliographic record
Abstract
The 2020 outbreak of the global COVID-19 pandemic imposed emergency remote teaching on adult English as a second language (ESL) programs globally, creating unprecedented challenges not only for language learners but also for instructors. Immense difficulties were produced in the collision between a biological hazard (the novel coronavirus) and the power-inflected social structures that organize language teaching in different locales. In this paper I explore some impacts of the pandemic on three instructors in the single largest adult ESL program in Canada, Language Instruction for Newcomers to Canada (LINC). Grounded in an account of the historical origins and development of the LINC program, a reflexive thematic analysis of instructor responses to vignettes of resonant challenges identified three major issues that were intensified by the pandemic: navigating digital inequities, balancing the teaching of digital literacies and language teaching in an accountability framework, and managing boundaries and expectations. These results are contextualized in the larger conversations around LINC and adult ESL programming globally, and some implications and new directions for the post-pandemic landscape now visible on the horizon are also considered.
 L’éclosion de la pandémie globale COVID-19 a imposé d’urgence l’enseignement à distance sur les programmes d’enseignement de l’anglais langue seconde (ALS) partout dans le monde, créant ainsi des défis sans précédent pour les apprenants de langues et leurs enseignants. Des difficultés considérables ont résulté de l’intersection explosive entre un danger biologique (le nouveau coronavirus) et les structures sociales basées sur le pouvoir qui organisent l’enseignement des langues dans plusieurs endroits. Dans cet article, j’explore certaines répercussions de la pandémie sur trois enseignants dans le plus grand programme d’enseignement de l’ALS aux adultes au Canada, le programme CLIC (Cours de langue pour les immigrants au Canada). Basée sur un récit des origines historiques et du développement du programme CLIC, l’analyse thématique réflexive des réponses des enseignants à des vignettes illustrant des défis évocateurs a identifié trois enjeux majeurs qui ont été intensifiés par la pandémie : naviguer les inégalités numériques, assurer l’équilibre entre l’enseignement des littératies numériques et l’enseignement de la langue dans un cadre responsable et gérer les limites et les attentes. Ces résultats sont contextualisés dans une discussion plus large sur le programme CLIC et les programmes d’enseignement d’ALS aux adultes autour du monde. Certaines implications et nouvelles directions pour le contexte postpandémie, désormais visible à l’horizon, seront également discutées.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.070 | 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 teacher head, 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".