Defining, Refining, and Enacting Religious Reflexivities in Pakistani-Canadian Muslim Families
Bibliographic record
Abstract
Political and popular discourse maintain Orientalist myths about Muslims as uniformly and fatalistically driven by a monolithic Islam, fueling a clash of civilizations. While researchers disrupt this Orientalist narrative by underscoring the presence of Muslim “reflexivity,” or the critical engagement with religious identities, beliefs, and practices, they nevertheless unintentionally reify a uniform Muslim reflexivity. This dissertation is the first empirically based study that demonstrates the social patterns of multiple forms of Muslim reflexivities. I highlight two patterns of reflexivities that relate to different approaches to religion: orthodox and heterodox. I further refine these patterns by highlighting how group and individual statuses shape social location, and thus subjectivity. I draw on theories of racialization and gender and I utilize a sample of 56 currently and previously married Pakistani Canadian Muslims to parse differences between orthodox and heterodox reflexivities and explore how divergent approaches to religion coincide with contrary patterns. These patterns are complicated by group identity for minorities within minorities (e.g., Shias) and by individual statuses (e.g., previously married women). In order to understand these divergent patterns, I extend the concept of Muslim reflexivity by incorporating a religious approach. Orthodox reflexive Muslim participants, who view one approach as correct, are preoccupied with authority given their identification with a marginalized minority group. Thus, they perceive ethnic boundaries as bright and gender boundaries as rigid. The focus of their reflexivity is dawat, or teaching others about the “true” Islam. This contrasts with heterodox reflexive Muslim participants, who view multiple approaches as correct. They do not perceive their minority group as being threatened, and thus do not seek out authority to legitimize their identity. In turn, they perceive ethnic boundaries as blurred, and maintain gender fluid attitudes and practices. The focus of their reflexivity is akhlaq, or having polite manners and ensuring mutually satisfying intimate relations. I conclude by discussing theoretical contributions and policy implications, cautioning against conflating categories of practice and analysis, and also problematizing liberal feminist approaches that pathologize Islam in efforts to ‘liberate Muslim women.’
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.012 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".