Islamic education in a multicultural context : the case of two educational institutions in British Columbia
Bibliographic record
Abstract
The purpose of this study is to increase understanding of Islamic education in Canada with an emphasis on how two educational institutions promote and maintain an Islamic worldview and identity in a secular pluralistic society. To achieve this goal, the study explores the nature and meaning of Islamic education in a national context, in which such education is caught between the edict to transmit and promote Islamic values on the one hand, and secular multiculturalism values on the other. This qualitative research uses an instrumental case study to provide an in-depth understanding of two participating Muslim schools in British Columbia, Canada. The case study, however, instrumentally offers understanding for Islamic education in a multicultural context. Findings from this research indicate that while Islamic educational institutions in Canada utilize various tools to nurture Islamic identity and worldview, they still face considerable internal challenges including limited resources and internal diversity. The internal challenges are exacerbated by external pressures in the form of Islamophobic sentiments fueled by poor media coverage. The dissertation recommends that Islamic educational institutions join the multicultural conversation with a genuine Islamic voice. Similarly, in order for these institutions to provide adequate Islamic education, they need to adopt targeted Islamization and embrace multiple identities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.051 | 0.008 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".