Calculating claims: Jewish and Muslim women navigating religion, economics and law in Canada
Bibliographic record
Abstract
Abstract This article presents an empirical study of Jewish and Muslim women who go through divorce in Canada, drawing on a ‘left law and economics’ methodology. Religious law and family law have long been considered outside the market and, as a result, are more rarely accounted for in the law and economics literature. According to dominant narratives, religious family law is experienced by women either as an exceptional form of oppression or as a form of spiritual religious identity. In this article, I apply a ‘left law and economics’ approach to deconstruct these notions. On the basis of my socio-legal fieldwork with Jewish and Muslim women in three Canadian cities, I identify the background formal and informal legal rules, social norms and distributional practices that help produce asymmetric bargaining locations for women. I employ the economic language of costs/benefits to illustrate the ways in which religious parties bargain strategically upon divorce, although these market claims are surprisingly underrecognised by the legal system. Such empirical knowledge helps disenchant the idea that religious law is systematically used as punishing forces that make women worse off economically or morally inferior. It also allows for a distributive analysis which reveals how husbands and wives negotiate economic resources, desires and day-to-day decisions in all kinds of fair and unfair ways, flying in the face of conventional narratives surrounding women and religion.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.036 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".