Organ donation and transplant: The Islamic perspective
Bibliographic record
Abstract
Islam is the second most practiced religion globally, and the number of Muslims in Western countries has been increasing due to recent trends in migration. Studies have shown that Muslims in the Western world have more negative attitudes toward organ donation and transplantation compared with individuals from other religious backgrounds. Multiple barriers have been postulated that may prevent Muslims from exploring organ donation or transplantation. We conducted a literature review with the goal of summarizing the opinions of major Sunni and Shia scholars and Islamic bodies about organ donation and transplantation, including their opinions and rulings on the neurological determination of death to inform healthcare professionals, community members, and leaders. We also identified factors and attitudes that may prevent members of the Muslim community from achieving equitable access to transplantation or from consenting to donate organs during life or after death. Key factors or concerns identified included: lack of information regarding organ donation, mistrust of the healthcare system, family opinions, sacredness of the body, lack of clear understanding of religious rulings, and opinions of religious leaders. Studies have suggested that partnering with religious leaders to address these concerns may help foster positive attitudes toward organ donation and transplantation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".