Cost-Effectiveness & Labour Market Outcomes in In-Vitro Fertilization
Bibliographic record
Abstract
This work uses two techniques to explore cost-effectiveness and labour market outcomes of provincial IVF funding policy. First, I conduct a cost-effectiveness analysis of IVF using a commonly accepted framework of Canadian health technology assessment from the perspective of the publicly-funded healthcare payer. Second, I construct a novel Conception Timing Model that represents the decision problem of a hypothetical Canadian individual who must weigh the tradeoff between having a child and the future income associated with furthering a career. The Conception Timing Model is developed under the rationale that the potential parent must incur an opportunity cost of lost wages when they decide to have a child. Results from the first approach suggests that a positive amount of IVF funding is cost-effective when constrained to the publicly funded healthcare payer perspective. The combination of the first and second approaches suggest that IVF policy may be used as both a health program and a social program that addresses inequities within the labour market. Results also speak to the importance of government ministries acting multilaterally to create effective welfare-improving policy.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".