Expanding Knowledge Systems in Teacher Education: Introduction
Bibliographic record
Abstract
One of the driving forces for this special issue on Expanding Knowledge Systems in Teacher Education has been the recognition that many existing teacher education programs operate from an unmarked norm of privilege that has a "semblance of naturalness that in itself defends it from scrutiny" (Hurtado & Stewart, 1997, p. 300).This naturalness, which evades scrutiny, continues to be used as a way to avoid recognition and inclusion of "hot" knowledge generated by women, peoples racialized as non-white, and other groups historically marginalized.Our argument is that it is necessary to set the context for a reality that teaching is a cultural exercise, embedded in at least one particular knowledge system and one particular set of values.We believe that the experiences of students in our programs should be predicated on an inquiry process that explores the idea that the Western (Canadian) knowledge system represents only one way of knowing and being.Preservice students as teachers will encounter many other knowledge systems and ways of being among their students, peers, and future teaching colleagues.During their undergraduate years, students should be taught to recognize, articulate, and integrate a basic Jennifer Kelly is an associate professor in theoretical cultural and international education.Her most recent research focuses on a socio-historical analysis of the relationship between racialization, immigration, and citizenship.She has several years of experience as a classroom teacher and preservice educator.Lynette Shultz is an assistant professor and Co-Director of the Global Education Network in the
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How this classification was reachedexpand
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".