Identity ‘issues’ and pedagogical silences: exploring teaching dilemmas in the northern Ontario kindergarten classroom
Bibliographic record
Abstract
As attention to social, cultural and physical diversities among student populations is steadily increasing in elementary/primary classrooms, the way in which teaching about those diversities is done necessitates a critical discussion. As most of the research on teachers’ responses to classroom diversity is conducted in big‐city, multicultural settings, this article departs from the norm by examining perspectives of teachers in a predominantly white community with mostly white students. The authors locate their exploratory research project in a Northern Ontario city and, using qualitative methods, consider the impact of teachers’ understandings of their own and students’ identities on their approaches to diversity. For these teachers to incorporate a diversity‐related topic into their teaching requires them to label it as an issue, which in turn is usually related to the presence or absence of certain identities in the classroom. The teachers struggle with the same/different conundrum and frequently turn their pedagogical dilemmas into pedagogical silences.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.051 | 0.054 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".