Sexual and Reproductive Rights from Qur'anic Perspective: A Quantitative Content Analysis
Bibliographic record
Abstract
The Qur'an, as the primary and main source of Islamic rules, provides a rich variety of human rights includingwomen’s rights. These rules are not static; they are dynamic and flexible in character. The flexibility of the rulesin Islam is intentional, as Islam was revealed for all people and for all millennia. It is an essential aspect ofQur'anic philosophy. Consequently, its jurisprudence must be capable of responding to widely diverse needs andproblems. To understand the Islamic stance on sexual and reproductive health rights, it is necessary to search theverses of the Qur'an more carefully. This study has provided an understanding of women’s sexual andreproductive rights in Qur'an from a human rights perspective.This study was conducted using quantitative content analysis of all verses of the Qur'an. After creating a codingscheme of Qur'an's verses, four categories related to the main areas of women’s sexual and reproductive rightsincluding sexual relationships, reproductive choice, prohibition of violence against women, and gender equitywere determined and their presence and frequency were identified. The MAXqda software, version 2007, wasused for organizing and managing the data. Descriptive analysis was used to summarize and describe data.More than 30 surahs and 93 verses of the Qur'an had various concepts in relation to sexual and reproductiverights. In general, concepts related to the women’s sexual and reproductive rights have been appeared 98 times inthe Qur’an. The most frequently reported categories were related to sexual relationships (31 times) andreproductive choice (27 times) and the least reported one was prohibition of violence against women (16 times).This study showed that the concepts related to sexual and reproductive rights have extensively appeared in theQur'an. Based on Qur'anic perspective, women in addition to autonomy have reproductive and sexual rights inorder to actualize of their human capacity.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".