Higher Education Teachers in Turmoil: Exploring how Variation in Coupling in Ontario ESL Units Impact Teacher Sensemaking
Bibliographic record
Abstract
Fierce competition for student tuition fees is prompting English as a Second Language (ESL) units in Ontario universities and colleges to adopt new business models, which are making some of those units more tightly coupled. As teachers and administrators attempt to address students’ needs within a recoupled governance structure, they may experience what scholars call “turmoil” – an erosion of longstanding meanings regarding their purposes and expectations in their organizational units. This analysis builds on established organizational concepts such as “sensemaking,” “turmoil,” “buffering,” and “the inhabited institution,” and applies them to a new context of changing administration in ESL units in universities and colleges. Using qualitative interviews, this study captures the reactions of instructors to tighter coupling in ESL units across Ontario public higher education institutions. Semi-structured interviews were conducted with 19 ESL instructors across 10 ESL units within higher education institutions in southern Ontario. These interviews explored teachers’ experiences with instances of turmoil and their subsequent sensemaking processes, which informed their actions and attitudes towards their professional practice. They found that when confronted with administrative impingement, teachers’ responses varied between resistance, compliance and in-between responses, which can be labelled as “personal decoupling” and “micro-politicking.” Also, as teachers grappled with greater bureaucratic control over the substance of their work and the casualization of many terms of their employment, they responded by either devising new ways to serve their students within new parameters in their workplaces or elected to leave their profession altogether.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".