Bibliographic record
Abstract
Purpose – The purpose of this paper is to describe divergent recent developments in provision of reproductive health services to North Americans. Design/methodology/approach – Narrative review. Findings – Two North American countries with very different histories present similar governance challenges today. The challenge is to provide all women with the full range of reproductive health options to which they are legally entitled now. In Canada, those contraception and abortion options are covered under the medical service plan insurance but not always available in convenient locations. In USA, those options are not uniformly covered under health insurance plans due to statutory limitations. In Canada, where federal law limiting abortion was struck down as unconstitutional, the leader of one of its three major federal political parties sees the way forward being to limit his party to pro-choice candidates. In USA, where new laws limiting abortion have been introduced at an unprecedented rate, the judiciary is being asked to define the way forward. Originality/value – Clinical governance needs to balance the moral beliefs of individual providers against the rights of patients to have their lawful choices available within reasonable convenience. Progress has been made but needs are still not adequately met, in these North American examples.
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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".