Donor Anonymity in Canada: Assessing the Obstacles to Openness and Considering a Way Forward
Bibliographic record
Abstract
This article discusses donor anonymity in Canada and the need for law reform in this area. Currently, assisted reproduction is regulated by both the provincial and federal governments, meaning this area is regulated in a piecemeal fashion. Disclosure of donor identifying and non-identifying factors is restricted to limited information, utilized only to keep statistical records. Due to the law limiting identifying information, donor-conceived persons struggle in their attempt to discover their genetic origins. Further, provincial family law does not recognize third party reproduction, which leaves modern family units unprotected. A definition of openness in gamete donation is given in Part II. Part III addresses the law-making and assisted reproduction difficulties arising from the division of powers. Part IV analyzes the potential impact of federal prohibitions on the purchase of sperm and eggs and whether disclosing a donor’s identity will negatively impact gamete supply in Canada. The final two sections discuss the failure of provinces to enact family laws which protect the parental status of intended parents and how past cases under the Canadian Charter of Rights and Freedoms have been challenging for donor-conceived persons. The authors propose that reform should be dealt with by the legislature in four areas: provincial family law reform where necessary; robust and meaningful public consultation; interprovincial cooperation if possible; and, consideration of law reform in other jurisdictions.
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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 | 0.027 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".