Muslim Studies in a Christian Theological School: The Muslim Studies Program at Emmanuel College in Toronto
Bibliographic record
Abstract
Abstract: This essay examines the development of a Muslim Studies program within Emmanuel College, a Canadian Christian theological school. The program has grown from a desire within the college to explore meaningfully the diversity associated with its social location in downtown Toronto and to participate responsibly in the important work of inter-religious dialogue. The story of the program's development is placed within an analysis of at least three areas offering challenges to the effort. Faculty members face significant obstacles in reshaping a curriculum within theological education that can address contemporary contexts of both Church and culture in a manner that includes intentional engagement with religious diversity. Within Christian history, a wide variety of methodological approaches have been developed to understand the nature of religious diversity in relation to Christianity. Each offers its own challenges to attempts to shape responsible encounters between Christianity and other world religions. Finally, the rich diversity within Islam existing within the social context of Toronto creates interesting challenges for a program in Muslim Studies intending to take expressions of religious faith seriously. The essay also examines wide-ranging rationales for why a Christian theological school would attempt to face these challenges in order to begin a program designed to provide educational opportunities for Muslims. In the final pages, the three major components of the program are described.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.031 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".