Bibliographic record
Abstract
The day the gavel was heard around the world: June 24, 2022.The Supreme Court of the United States, having just overturned Roe v. Wade, set a precarious precedent: prioritizing individual politics over the people.I was upended by these headlines just prior to starting my rural family medicine rotation in Ontario, Canada.Unbeknownst to me at the time, I was about to witness how Canadians are not as astray from the judicial atrocities occurring south of the border.In this Correspondence, I will describe the barriers that the Catholic Health Alliance of Canada (CHAC) continues to erect for patients.I was stationed at 1 of 129 CHAC facilities across Canada, which practises care as per the Health Ethics Guide. 1 Last updated in 2012, the guide's purpose is to ". . .provide guidance around advances in science and medicine. . . in the Gospel message of Jesus."Principally, the communities these hospitals serve are not privy to amenities they are legally entitled to.This translates to individuals having reduced accessibility to counselling regarding gender-affirming care, contraception, fertility, medical assistance in dying (MAiD), and innovations derived from gametes, embryos, and fetuses. 1 During my first week, consequences of this reality greeted me.An inpatient, diagnosed with interstitial pulmonary fibrosis and requiring 9L of oxygen, sought MAiD.Through this case, I learned the steps to the subtle tango between physician and patient in an institution where Canada's laws don't reach.In the dead of night, after my attending physician explained why they could not honour this request, the inpatient made the decision to take matters into their own hands.They quietly, and with what I can only imagine was with great disdain, removed their oxygen, suffocating themself; a victim of needless agony.In Ontario, CHAC institutions account for 15% of health services.Why, in a country that prides itself on multiculturalism, is a singular belief system limiting medical access on religious grounds?Why, when the number of Canadians who identify as religious has fallen from 90% in 1985 to 68% in 2019 (and the percentage who identify as Catholic having halved to 29%), are we choosing to ignore an ever-growing disparity in care? 2 It would be ignorant to disregard these policies' unequal impacts.Women and individuals with uteruses
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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 | 0.032 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.023 | 0.034 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.055 | 0.068 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".