Religion in the Abortion Discourse in Singapore: A Case Study of the Relevance of Religious Arguments in Law-Making in Multi-Religious Democracies
Bibliographic record
Abstract
I … appeal to hon. Members to face up to the challenge on this important social issue and give their full support to the Bill. I do hope that they will not falter just because of some pressure, social or otherwise, brought to bear on them by some minority groups outside who, on account of their religious dogmas, desire to impose their will on the majority… I am certain that the opposing stand to this Bill taken by this minority group will also in the course of time end up in the dustbins of history. Abortion, along with same-sex unions, is perhaps one of the world's most polarizing issues today. Laws on abortion vary across different jurisdictions, from prohibiting abortion under all circumstances to freely allowing it without restriction as to reason. Unlike rights such as freedom from torture or of speech, failure to recognize abortion rights is not necessarily the product of illiberal governments known to abuse human rights, nor is allowing abortion indicative of a good human rights record. Extensive rights to terminate a pregnancy may be symptomatic of a government's policy for population control, as in the case of China, or it may be an expression of the liberal philosophy of autonomy, as in the case of Canada.
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 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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| 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".