What Should Preservice Teachers Know about Race and Diversity? Exploring a Critical Knowledge-Base for Teaching in 21st Century Canadian Classrooms
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
Anecdotal and empirical evidence suggest that how teachers construct and interpret issues of race and diversity impacts significantly on their interactions with students from diverse backgrounds. At the same time, research shows that teacher education programs do not pay as much attention as would logically be expected given that many Canadian teachers will spend a good part of their career in racially and culturally heterogeneous settings. Conceptually grounded in critical race theory- a framework with increasing application in education, this paper explores the knowledge-base that preservice teachers require for successful teaching in a pluralistic society. A central argument in the paper is that a deep understanding of, and knowledge about race and diversity (beyond cursory familiarity) should be one of the required outcomes of preservice education.
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 | 0.003 | 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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