Supporting a Collective Vision of Ethical Professionalism: Knowledge Mobilization through Experiential and Inquiry-Based Processes
Bibliographic record
Abstract
Abstract The engagement of the teaching profession and members of the public in provincial knowledge mobilization efforts was essential in supporting the enactment of a Collective Vision of Ethical Professionalism throughout Ontario classrooms, schools, school boards and teacher education. This shared pursuit of College Council members, College staff, the profession and the public were further strengthened through the construction of teacher education resources and policies based on the lived practice of educators and explored through experiential and inquiry stances. These teacher education resources and continuing teacher education resources helped to support knowledge mobilization within professional practice, teacher education and leadership development. These collaborative mobilization knowledge efforts privilege the voices, perspectives and practices of educations and enable them to be used for teacher education policy and andragogy.
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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 | 0.060 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.017 | 0.065 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".