Hidden from view: Canadian gestational surrogacy practices and outcomes, 2001-2012
Bibliographic record
Abstract
This paper raises some troubling questions about the fertility treatments provided to Canadian gestational surrogates, women not genetically related to the child that they carry. Using information published between 2003 and 2012 by Canada's Assisted Reproduction Registry, the paper traces the growing incidence of births to gestational surrogates. The transfer of more than one embryo increases the chance of pregnancy and the incidence of multiple births, and while the incidence of multiple births has declined overall since 2010, gestational surrogates consistently experience a higher proportion of multiple births and experienced higher levels of multiple embryo transfers. In 2012, just 26% of gestational surrogates received a single embryo transfer compared to 47% of other in vitro fertilisation (IVF) patients. The paper suggests that renewed attention needs to be paid to the counselling provided to gestational surrogates and treatment consenting mechanisms used by IVF clinics and that review of the 2007 Canadian Medical Association surrogate treatment guidelines is warranted. Finally, the paper describes the difficulties in obtaining accurate data about Canadian assisted reproductive medicine. Without good data, it becomes far more difficult to identify the possibility of potentially harmful practices.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".