Bibliographic record
Abstract
The Canadian province of Quebec recently amended its Health Insurance Act to cover the costs of In Vitro Fertilization (IVF). The province of Ontario recently de-insured IVF. Both provinces cited cost-effectiveness as their grounds, but the question as to whether a public health insurance system ought to cover IVF raises the deeper question of how we should understand reproduction at the social level, and whether its costs should be a matter of individual or collective responsibility. In this article I examine three strategies for justifying collective provisions in a liberal society and assess whether public reproductive assistance can be defended on any of these accounts. I begin by considering, and rejecting, rights-based and needs-based approaches. I go on to argue that instead we ought to address assisted reproduction from the perspective of the contractarian insurance-based model for public health coverage, according to which we select items for inclusion based on their unpredictability in nature and cost. I argue that infertility qualifies as an unpredictable incident against which rational agents would choose to insure under ideal conditions and that assisted reproduction is thereby a matter of collective responsibility, but only in cases of medical necessity or inability to pay. The policy I endorse by appeal to this approach is a means-tested system of coverage resembling neither Ontario nor Quebec's, and I conclude that it constitutes a promising alternative worthy of serious consideration by bioethicists, political philosophers, and policy-makers alike.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.067 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".