The Requirements of Introducing the Common Property System to the Iranian Matrimonial Regime with a view to the Quebec Matrimonial Regime
Bibliographic record
Abstract
legal regimes differ in outlining the method of contribution to the household, financial maintenance, and the division of property after separation/divorce. Some legal regimes, following the CEDAW’s regime, look for an egalitarian regime which rules for similar rights and responsibilities for both parties and partial community of properties between spouses through which economic advantages and disadvantages related to marriage and dissolution of marriage should be born equally by both parties. Another group of legal regimes establishes separation of properties as the guiding principle for marital economic relationship in which the expenses should be borne by men as the heads of the household and women should be compensated for her unpaid contribution to the household. This research will focus on Iran’s legal system, which follows Sharia (Islamic law) in separation of properties and ruling for compensation of unpaid contribution of women to household. The research compares Iran’s legal system and Quebec’s laws as an example of egalitarian regime and evaluate if Iran’s family law could integrate community regime in its family law with regard to the Sharia principles and its Islamic family law. And which criteria should be considered by Iranian legislator if desire to adopt community regime.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".