Bibliographic record
Abstract
This book poses the following questions: How do accommodative arrangements advocating cogovernance by state and society in legally plural societies impact on the interactions between and within religious groups and other societal bodies? How do they shape gender equality in the family? What is the nature of state-society interactions in the adjudication of religious laws in legally plural societies? The study aims to describe, understand, and, in the end, explain the functioning of the Indian policy of legal pluralism as an accommodative measure in the governance of marriage and divorce among Hindus and Muslims. The Indian state has adopted what I call a shared adjudication model in which the state and a broad range of societal bodies share adjudicative authority. In other words, the Indian state, in the governance of religious family law, adopts the strategy of “regulated autonomy” by which it incorporates religious groups into the governance of the family and circumscribes their sphere of autonomy. This strategy is an outcome of the Indian state's desire to shape the family and gender from above while balancing the plural demands of groups. The model has been crafted from above but it been creatively interpreted, shaped, and used by societal actors and bodies, its boundaries challenged, changed, and stretched on the ground. Given that the Indian state recognizes state and nonstate laws and allows adjudication in formal and informal arenas, how do we distinguish between state and societal laws and characterize interactions between official and unofficial legal arenas?
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.231 | 0.099 |
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".