Marriage Pluralism in the United States: On Civil and Religious Jurisdiction and the Demands of Equal Citizenship
Bibliographic record
Abstract
“Legal pluralism” is hot, particularly in family law. As family law and practice in the United States have become global due to the globalization of the family, some argue it is time for U.S. family law to embrace more legal pluralism so that civil government would cede jurisdictional authority over marriage and divorce law to religious communities. They point to forms of pluralism already present in U.S. family law, such as covenant marriage (available in three states) and New York’s get statutes. They suggest the U.S. should learn from how many other nations allocate jurisdiction over marriage and divorce law (for example, systems of personal law, in which religious tribunals have such jurisdiction). In this chapter, I argue that an exercise in comparative law does reveal many different ways of allocating jurisdiction over family law, but does not answer the normative question of whether these are good models for U.S. family law. Challenging the call for a “multi-tiered” marriage, I analyze what form of marriage pluralism in the U.S. is sought and what might be motivating this demand. I examine differing views about whether there should be congruence between religious and civil marriage, illustrating with the controversy over same-sex marriage. I raise a normative concern over tensions between religious doctrines and key commitments, values, and functions of civil family law, illustrating with how state courts in the U.S. now navigate those tensions when asked to enforce terms of religious marriage contracts and other religious law. I am also skeptical as to whether a more pluralistic legal system can adequately protect the equal citizenship of women. Nearly every foreign example that proponents of jurisdictional pluralism in family law offer raises troubling question about how to reconcile sex equality with religious freedom. Feminist scholars highlight the importance of claims of national and constitutional citizenship as a strategy for redressing sex inequality, even as they affirm the value of membership in religious and cultural groups. Finally, I ask what lessons we might learn about legal pluralism from the recent controversy over religious family law arbitration (or “sharia arbitration”) in Ontario.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".