Hannay, L., Wideman, R., & Seller, W. (2010). Professional learning to reshape teaching. Toronto, ON: Elementary Teachers’ Federation of Ontario.
Bibliographic record
Abstract
This book is about professional change from the bottom up—that is, it is about professionals taking charge of their own knowledge creation in order to create lasting change in their practice. In a very real sense, this text provides an avenue for individuals to do what Whitehead (1989) described as engaging in “Action Reflection” in order to build a “living educational theory” for ourselves as professionals learning about our craft across the years of our careers. The action reflection cycle described by McNiff (2000) seems to me to be embedded in this text as a guide to furthering our own professional development and direction. She notes five points: I, the individual, am central to the process; I am learning first about myself in order to change a social situation; I am not aiming for closure but ongoing development; the process is participative; and, the process is educational (p. 203). Hannay, Wideman and Seller bring out these points by encouraging educators to engage in a process of constructing their own knowledge through collaboration with colleagues and through the use of inquiry, much as we advocate for this with students in our care at all levels of learning. In this model, leadership becomes a shared activity “with the goals of the process
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".