Empirical Factors of Takliq Talaq Through Electronic Media in View of Positive Law And Islamic Law
Bibliographic record
Abstract
The words talaq are usually expressed verbally or directly by the husband to his wife, so that the wife can directly hear the expression of the word divorce from her husband. But along with the era of globalization, communication media in the form of cellphones turned out to be used by some husbands who were disappointed with their wives as a medium to declare divorce. The phenomenon of talaq through electronic media raises legal questions about its validity in terms of Islamic law. Based on the provisions of Article 65 of Law No. 7 of 1989 junto article 115 of the Compilation of Islamic Law (KHI) it is explained that divorce can only be carried out in front of a panel of judges in a court session. Divorce through social media reaps many pros and cons among scholars about its validity. Talaq through mobile electronic media either only in the form of sound or accompanied by its form in the form of pictures (video calls) in sharia talaq is declared as legal talaq, talaq is carried out via SMS, so scholars position this problem the same as the issue of divorce through writing. Meanwhile, according to the law on marriage in Indonesia, it is only declared valid if it is pronounced in a religious court.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".