Bibliographic record
Abstract
Much of the literature on Islamic Social Institutions (ISIs) has argued that these institutions are recruiting grounds for the poor. Clark (Univ. of Guelph, Ca.), through case studies of ISIs in Egypt, Yemen, and Jordan takes this notion to task. She argues that the vertical networks (i.e. across classes) created through ISIs are weak, that the important social networks are the horizontal ones within the middle class, and that this is in keeping with social movement theories. In addition, she demonstrates how a strategy of solidifying middle class networks,one that is demanded by the operational needs of ISIs, may actually work to discredit Islamic movements that support these ISIs in the long run. Finally, she argues that ISIs do not necessarily seek radical transformation of society and that there is nothing obviously Islamic in their provision of services. Her argument is clear and easy to follow, and the case studies are rich with supportive data. However, in some respects, the case study of the Islah Charitable Society in Yemen, differs from the others and raises questions about her contentions, particularly about the Islamic nature of ISI activities. Summing Up: Recommended. Advanced-level undergraduates and graduates, specifically those interested in civil society in the region and Islamism.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".