In pursuit of being Canadian: examining the challenges of culturally relevant education in teacher education programs
Bibliographic record
Abstract
This article is about an ongoing initiative that addresses the challenges confronted by teacher candidates to whom English is an additional language and whose cultures are considered different from those of the Canadian mainstream. The initiative is a seminar, Language and Cultural Engagement, in which teacher candidates are prepared for practice teaching through discussions and presentations about diversity, language, and culture; video recorded, peer and teacher analyzed ‘rehearsal’ classroom teaching in a partnership school; and Enriched English as a Second Language lessons. The article is based on data collected through surveys at the beginning and end of the seminar, as well as on instructors' reflections working with teacher candidates from diverse cultural backgrounds dealing with the nuances of the Canadian classroom. Three concerns, concern for authority, language, and cultural acceptance, which were identified as impacting teacher candidates' practice are examined. In addition, the degree to which these concerns were reduced through the seminar is presented. Nonetheless, the concern for cultural acceptance remained unchanged and was identified by teacher candidates as fundamentally important to how they were viewed by their host teachers as knowledgeable, qualified professionals.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.042 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".