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Record W4403351798 · doi:10.61838/kman.isslp.3.3.7

Comparative Analysis of Spousal Rights in Imami Jurisprudence, Iranian Law, and Selected Countries

2024· article· en· W4403351798 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicLandscape and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLandscapingArchitectural engineeringLandscape designGarden designGeographyCivil engineeringAestheticsEngineeringArtEcology

Abstract

fetched live from OpenAlex

According to the Iranian Civil Code, as soon as a marriage contract is validly concluded, marital relations are established between the parties, and the rights and duties of the spouses toward each other are defined. These rights and duties vary significantly across the laws and legal systems of different countries. This study employs a descriptive-analytical method to examine the comparative rights of spouses under Iranian law, rooted in Imami jurisprudence, and the laws of selected countries (such as Canada, the United States, and European countries like France and the United Kingdom). The findings reveal fundamental differences between spousal rights in Iran and the selected countries, except for areas such as the mutual obligation for good conduct and child custody rights. One significant difference lies in mahr (dowry), which is a critical financial right of spouses in Iran, where the wife owns the mahr as a debt owed by the husband. In contrast, countries like the United States, Canada, and many European nations do not recognize the concept of mahr but instead apply marital property division laws. Additionally, rights such as the husband’s authority as head of the family, the wife’s right to work, and the unilateral right of divorce (exclusively held by the husband) differ from the selected countries, which base spousal rights on gender equality, granting equal and shared rights and responsibilities to both spouses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.253
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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