“Retrospective Removal of Gamete Donor Anonymity: Policy Recommendations for Ontario Based on the Victorian Experience”
Bibliographic record
Abstract
This paper undertakes a comparative analysis of the gamete-donor anonymity schemes in Ontario, Canada and Victoria, Australia. As of March 1, 2017, Victoria became the first jurisdiction in the world to retrospectively remove gamete-donor anonymity. Conversely, donor anonymity remains protected in Ontario, largely through statutory silence. While many donor conceived individuals are calling for other jurisdictions to follow suit and retrospectively abolish anonymity, an in-depth analysis of Victoria’s policy-making process suggests that Ontario should not take a similar course of action. This conclusion is based on the inherent issues with retrospective legislation, the historical differences between the two jurisdictions in overseeing gamete donation, the Victorian government’s inconsistent reliance on evidence, and the ill- suited reasoning used to justify Victoria’s policy decision. In lieu of enacting retrospective legislation, this paper recommends that Ontario should increase public education and create a voluntary, provincial donor registry. Based on a relational approach, these steps are more conducive to harmonizing the complex, interconnected interests at play and to supporting healthy relationships in whatever form they may take.
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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 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| 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".