Conscientious Objection and the Provision of Abortion at Late(r) Stages of Pregnancy
Bibliographic record
Abstract
This essay concerns a theoretical issue that has the potential to arise in the provision of late(r) term abortion in particularly liberal or highly permissive jurisdictions, meaning those that do not require criteria to be met if the procedure is to be lawful. By not establishing criteria that restrict the provision of late(r) term abortion the procedure is rendered lawful “on demand”, at least in principle. This raises the possibility that healthcare professionals may encounter specific requests for terminations that they consider morally unjustified, meaning that some might seek to “opt-out” of provision in such cases by appealing to the notion of conscientious objection. The existing literature would likely frame such appeals to be instances of selective conscientious objection. Whilst I argue that this notion is flawed, I also suggest that there is a need to recognise a degree of nuance in the ethical positions held by healthcare professionals when it comes to the provision of abortion at late(r) gestational (st)ages in jurisdictions that adopt highly permissive forms of regulation. However, given that conscientious objection should not be permitted to obstruct provision of legally permitted interventions, there is a moral imperative to ensure access, and healthcare systems must take steps to ensure provision. Whilst it may be possible, it is unlikely to be simple, and it may auger against establishing legalisation that is highly permissive.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.064 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".