Bibliographic record
Abstract
In Politicizing Islam, Z. Fareen Parvez offers a timely new approach to studying Islamic revival movements in cross-national perspective. Based on two years of ethnographic fieldwork and thirty-nine interviews with Muslim activists, community leaders, politicians, teachers, and middle- and working-class residents in Lyon, France and Hyderabad, India, the study departs from previous work by attending to the social and economic—rather than simply the religious—conditions that give rise to revivalist politics. The result is a book that takes seriously the everyday practices of Muslim communities, rather than reading those practices through the discourses imposed “from above” by states. The core argument of Politicizing Islam is that states’ differing regimes of secularism have bearing on the relationships among middle- and working-class Muslims, with significant consequences for the aims, tactics, and orientations to state power adopted by Islamic revival movements. In France, Parvez argues, the predominance of an assimilationist and restrictive secularism has led middle-class Muslim organizations to direct their mobilizing efforts toward the elusive goal of obtaining state recognition of Islamic religious beliefs and practices. This narrow emphasis on recognition has in turn inhibited the pursuit of a radical redistributive agenda, ultimately sullying inter-class relations. Isolated from their middle-class counterparts, subaltern Salafist Muslims inhabiting impoverished city suburbs have responded by adopting what Parvez calls an “antipolitics”: a political practice that focuses on faith and self-protection, and seeks to expand the boundaries of the private sphere against an intrusive state. In India, by contrast, where the government has pursued a pluralist and flexible secularism, middle- and working-class Muslims have joined together in a project to achieve greater economic redistribution. Through cross-class coalitions, subaltern Muslims in that setting have succeeded in forging political communities—sustained to a large extent by women—that alleviate poverty without demanding resources from the state.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| 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".