Gender, religion and the ‘developmentalization’ of male Muslim imams in Bangladesh
Bibliographic record
Abstract
In this article, I explore how entanglements between two international development organizations, the state and male Muslim imams or congregational prayer leaders, in Bangladesh from the early 1980s to the present time combine in the ‘developmentalization’ of thousands of male imams as mobilized, institutionally fixed repositories of male Islamic authority. Following Arturo Escobar’s argument that development discourse organizes and manages the South through problematizing specific issues that development apparatuses then proceed to resolve, I suggest that male imams are mobilized in order to satisfy specific contingencies elaborated by, among other things, development itself. Drawing on textual analysis and empirical work with development policymakers and imams in Bangladesh, I analyse the origins, conditions and exigencies under which male imams become partners in development activity, including programmes that target women’s reproductive health choices and provide intimate, personal contraceptive care. I adopt a critical feminist development studies perspective, wherein gender concerns and women’s issues are a critical consideration of development interventions in the South, to explicate how both gendered resistance and complicity are evident in complex ways within these alliances. My research suggests that although evident in Bangladesh, imam mobilizations are facilitated by linkages at local, national, regional and transnational levels.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".