Origin of “Conscientious Objection” in Health Care: How Care Denials Became Enshrined into Law Because of Abortion
Bibliographic record
Abstract
The United Kingdom was the first country to legalize the refusal to provide health care in the name of "conscientious objection", allowing doctors to refuse to provide abortions based on personal or religious beliefs.A historical review into the origins and motivation behind the "conscientious objection" clause in the 1967 Abortion Act found that Parliamentarians and the medical profession wanted to preserve doctors' authority over patients, protect objecting doctors from liability, and appease religious anti-abortion beliefs.These factors point to an unprincipled basis for the introduction of "conscientious objection" into healthcare, which ultimately came at the expense of patients' rights and health. The "conscience clause" also represented a negation of basic ethical directives in medical practice including patient autonomy and physicians' fiduciary duty to patients. The term "conscientious objection"- borrowed from the military but misapplied to healthcare - helped mask the practice as a moral "right" of doctors, even while it disregarded patients' health and dignity.Refusing to provide treatment on the basis of "conscience" is harmful and discriminatory, and should be phased out gradually using disincentives and other measures to encourage objectors to choose other fields.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.095 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".