Autonomous Motherhood and the Law: Exploring the Narratives of Canada’s Single Mothers by Choice
Bibliographic record
Abstract
In the past three decades, single mothers by choice (SMCs) have emerged as a new and rapidly growing component of Canada's single mother population. SMCs are women who choose to have a child, usually via some form of assisted conception, with the intention that they be their child's sole parent. While SMCs are part of an increasing number of non-normative family configurations in Canada, they pose some unique social and legal questions. However, unlike some other non-normative families, such as lesbian and gay families, SMCs have received very little academic attention and almost none pertaining to the role of law in their lives. In an effort to fill this knowledge gap, this article presents the findings from a small interview-based study of Canadian SMCs that explored the ways in which the pre-conception decision-making and post-birth experiences of the mothers were shaped by law. Though the law was rarely an overt presence in the women's lives, they identified three aspects of becoming and being an SMC that were nonetheless shaped by law: (i) the pre-conception period during which they were forced to navigate a largely unregulated fertility industry; (ii) when making decisions about the type of sperm donor with which to conceive; and (iii) once they had their child, the ways in which everyday activities were sometimes complicated by a legal system that assumes a two parent, biological family.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.021 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| 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".