Religion, diversity, and teacher education: The role of religious literacy in Alberta’s teacher education programs
Bibliographic record
Abstract
Alberta has seen a rapid influx in new immigrants in recent years, leading to greater ethnic and cultural diversity. In 2016 federal census, new immigrants comprised 17.1% of Alberta’s population while visible minorities made up 23.5% of the provincial population (Statistics Canada 2016). Given these recent demographic shifts, Alberta’s K-12 classrooms are in dire need of teachers who are prepared to engage with cultural diversity of all sorts, including religious diversity, in their classrooms as they endeavor to educate future citizens. Recent scholarship has noted that current K-12 teachers feel unprepared and lack professional development opportunities to teach religion or engage effectively with religious diversity in their classrooms (Gardner, Soules, and Volk, 2017; Patrick et al, 2017). This paper will review current teacher education curricular documents with the aim of determining how teacher education programs in Albertan universities prepare preservice teachers to engage with religious literacy as an educational aim for civic competency.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".