Making Tradition Possible in Canada: Islamic Organizations and the Problem of Commitment
Bibliographic record
Abstract
This dissertation examines the hitherto unrecognized part that Islamic organizations play in the ethical projects of Canadian Muslims. More specifically, it ethnographically explores two national Islamic charities, based in the Greater Toronto Area (GTA): the Islamic Society of North America (ISNA) and the Muslim Association of Canada (MAC). Rather than study their “nature” or how they work, I focus on the aspirations that shape what they do and imagine their role to be. I locate organizational self-understanding in the perspectives of the people that animate them—the directors, executives and volunteers—which I consider alongside the discursive and material forms that organizations take in by-laws, websites, social media, services, events, and spaces. For my interlocutors, the modern world is increasingly characterized by the normalization of heterogenous modes of being. Canada epitomizes this phenomenon as a secular liberal society where pluralism is not just a demographic reality in the GTA, but is also a national policy, civic ideology, and shared sensibility. In this culturally fragmented context, my interlocutors consider it to be challenging to live Islam as a complete way of life, private and public, everywhere and all of the time. This full Islamic commitment, indexed by a public-facing capacity to discourse and act readily, fluently, and topically from an Islamic paradigm, is considered to be a burden too great for individuals to bear alone. Examining the organizational strategies, deliberations and work at ISNA and MAC, I argue that the form of the Islamic charitable organization, with its extensive resources and reach across the micro and macro levels of society, is posited as an instrument of tarbiyah or Islamic rearing and education and as a necessary buttress for living Islamic forms of life in public space: in other words, a solution to the problem of commitment. Weaving threads from the anthropology of Islam into uncharted territory in the study of Islam and Muslims in Canada, I highlight the overlooked roles of Islamic organizations in the ethical aspirations of Canadian Muslims to ultimately argue that they are deserving of much more focused ethnographic attention and anthropological analysis.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.064 | 0.030 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| 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".