Shari’a, InshAllah: Finding God in Somali Legal Politics by Mark Fathi Massoud
Bibliographic record
Abstract
Shari’a, InshAllah: Finding God in Somali Legal Politics (“Shari’a InshAllah”), written by Mark Fathi Massoud, professor of politics and legal studies at the University of California, Santa Cruz, is a compelling and fascinating work chronicling the relationship between law, religion, and politics in the context of Somalia’s recent history. In this book, Massoud explores the inextricability of religion from Somali legal politics as the country grapples with its colonial and post-colonial legacies and relationships to power in a society where God serves as a conduit for both faith and aspirations of self-determination. In a region where distrust of Western institutions and fears of authoritarian rule dominate state and capacity-building exercises, Massoud demonstrates how activists, lawyers, lawmakers, dictators, rebel groups, militants, and international aid organizations contend with competing sources of law, power, and politics in a fractured state. He further demonstrates the potential of Shari’a (i.e., Islamic law) to bridge divides across the most diverse of actors in order to produce a common logic of deference, submission, and adherence to the Rule of Law. Perhaps most critically, Massoud investigates the position of Shari’a in global discourse and how Western conceptions of Shari’a (seemingly influenced by orientalist tropes, imperialism, and Western hegemony and exceptionalism) give rise to misapprehensions of its utility, flexibility, necessity, and effectiveness in societies where Islam transcends political disagreements, clan affiliation, and personal identity.
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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 | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".