The development and impact of teachers’ collective agency during Covid-19: insights from online classrooms in Canada and China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Teacher education programmes are embedded in both higher and K-12 education contexts. This study explores how collective teacher agency is developed and manifested within two online teacher education courses in a Canadian university and a Chinese university, respectively, under the Covid-19 pandemic context. Employing a digital ethnographic approach, this study reveals that: 1) the structural changes caused by the pandemic create common goals for collective teacher agency to develop; 2) collective teacher agency is motivated by caring for student well-being and honing of teaching skills; and 3) the asynchronous course structure hindered Chinese student teachers’ collective efforts to improve teaching but afforded the Canadian group’s greater collective agency in connecting with their schools. Importantly, this study highlights the role of emotions in facilitating collective agency and argues that emotions are an integral but often overlooked part of teacher agency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it