Willingness to pay for ovulation induction treatment in case of WHO II anovulation: a study using the contingent valuation method
Bibliographic record
Abstract
Thomas G Poder,1 Jie He,2 Catherine Simard,3 Jean-Charles Pasquier4 1UETMIS and CRCHUS, CHUS, Sherbrooke, QC, Canada; 2Department of Economics, GREDI, University of Sherbrooke, QC, Canada; 3Department of Obstetrics and Gynecology, CH of Chicoutimi, affiliated to CHUS, QC, Canada; 4Department of Obstetrics and Gynecology, CHUS, Sherbrooke, QC, Canada Objective: To measure the willingness to pay (WTP) of women aged 18–45 years to receive drug treatment for ovulation induction (ie, the social value of normal cycles of ovulation for a woman of childbearing age) in order to feed the debate about the funding of fertility cares.Setting: An anonymous questionnaire was used over the general population of Quebec. Participants: A total of 136 subjects were recruited in three medical clinics, and 191 subjects through an online questionnaire.Method: The questionnaire consisted of three parts: introduction to the problematic, socioeconomic data collection to determine factors influencing the formation of WTP, and a WTP question using the simple bid price dichotomous choice elicitation technique. The econometric estimation method is based on the “random utility theory.” Each subject responding to our questionnaire could express her uncertainty about the answer to our WTP question by choosing the answer “I do not know.”Outcome measure: The WTP in Canadian dollars of women aged 18–45 years to receive drug treatment for ovulation induction.Results: Results are positive and indicate an average WTP exceeding 4,800 CAD, which is much more than the drug treatment cost. There is no evidence of sample frame bias or avidity bias across the two survey modes that cannot be controlled in econometric estimates.Conclusion: Medical treatment for ovulation induction is highly socially desirable in Quebec. Keywords: WTP, fertility, drug therapy
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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".