Transforming Teacher Education Thinking: Complexity and Relational Ways of Knowing
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
In order that teacher education programs can act as significant scaffolds in supporting new teachers to become informed, creative and innovative members of a highly complex and valuable profession, we need to re-imagine ways in which teacher education programs operate. We need to re-imagine how courses are conceptualized and connected, how learning is shared and how knowledge, not just “professional”, but embedded knowledge in authentic contexts of teaching and learning is understood, shaped and re-applied. Drawing on our study of a locally developed program in secondary teacher education called Transformative University of Victoria (TRUVIC), we offer a relational approach to knowing as an alternative to more mechanistic explanations that limit teacher growth and development. To ground our interpretation, we draw on complexity theory as a theory of change and emergence that supports learning as distributed, relational, adaptive and emerging.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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