Bibliographic record
Abstract
Who a child's parents are is a question that might be answered differently by a jurist than by the child concerned. Law directs us to look at particular rules to determine parentage. Yet these rules might not reflect actual relationships within families that extend care, nurturing and support to children, particularly when conception has occurred through assisted procreation. This article is prompted by the discordance between legal and social locations of parenthood in these contexts. Examining Canadian common law and Quebec civil law, it considers whether legal strictures imposed on families created through assisted reproduction hinders children from developing relationships that foster self-awareness and a meaningful sense of ‘place’ within their communities. Part I considers the manner in which law searches for parents and finds them, discussing cultural and social forces at play in shaping parent–child relationships. Part II sets out a taxonomy for understanding law's location of parenthood where children have been conceived through donated genetic material or surrogacy. Part III highlights factors that have driven these assessments of parental status, namely, biological connections, the intentions of participants in assisted procreation arrangements, and social relationships formed with the children produced by such arrangements. Potential difficulties with relying on these factors are identified, signalling the need for a more coherent and equitable framework for determinations of parental status.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".