From Impetus to Engagement: Ecological Perspectives on Content Faculty Agency in CLIL Collaborations at a Canadian University
Bibliographic record
Abstract
This qualitative case study explores the experiences of content faculty (CF) participating in interdisciplinary collaborations for Content and Language Integrated Learning (CLIL) in Canadian higher education. Using an ecological lens, this study examines the motivations, enactments, and contextual factors shaping agency across three disciplinary cases. Data from semi-structured interviews reveal that collaborative dynamics and the enactment of agency are shaped by disciplinary expertise, interpersonal relationships, and the interplay of personal histories, future aspirations, institutional structures, and professional contexts within the ecologies of these partnerships. They underscore the importance of recognizing faculty contributions and addressing institutional barriers to strengthen collaborative efforts. In addition to extending CLIL research beyond predominantly European and Asian contexts, the findings offer insights into how institutions can better support the language and literacy development of their multilingual students.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.055 | 0.044 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".