How Do Anti-abortion and Abortion Rights Groups Deploy Ideas About Islamic in Their Activism Regarding Abortion
Bibliographic record
Abstract
Abortion is a hotly debated topic among Muslim communities, yet not many people outside of Muslim communities noticed this controversy, assuming that all Muslims hold similar opinions. In this paper I seek to answer the question: How do anti-abortion and abortion rights groups deploy ideas about Islam in their activism regarding abortion? I analysed the language those organizations use when describing Muslim communities and Muslim views, in order to learn their opinion. I found that a majority of those organizations did not include arguments from both sides, and almost all the Anti-Abortion Websites included generalizations of the Muslim community, and uses the Islamic Religion’s conservative factors as their method to persuade more Muslim people to join their stance on abortion. My research can serve as a contribution to research on broader questions such as: Why do a significant amount of people worldwide have very monolithic and stereotypical impressions on the Islamic religion? How influential is religion to a country's justice system and social morals? Those are all relevant question that matters significantly to our world, I hope that my research can have an impact and perhaps inspire further research into these questions.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".