Constrained Choices: Navigating Agency and Social Structures in Sperm Donor Selection
Bibliographic record
Abstract
This study examines how intended parents in Canada navigate the process of sperm donor selection under institutional, interpersonal and material constraints. Drawing on qualitative interviews with parents (N = 40) from diverse family configurations (heteroparental, lesboparental and soloparental), it explores how donor selection is not a purely autonomous decision but a negotiated practice shaped by regulatory ambiguity, limited donor availability, emotional investments and intracouple dynamics. Grounded in negotiated order theory, the analysis emphasises the provisional, iterative nature of decision-making within fertility clinics and donor databases-understood as intersecting social worlds within a broader reproductive arena. Findings show that initial parental preferences (e.g., donor resemblance, identity disclosure and medical history) are shaped by normative kinship ideals and are often compromised over time due to structural constraints or evolving priorities. This study contributes to the sociology of health and illness by reconceptualising donor selection as a situated negotiation, where choice is exercised relationally and within unequal institutional landscapes. It also identifies avenues for future research and policy reform, including clearer clinical guidance, improved access to donor information and stronger alignment with donor-conceived persons' rights.
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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 | 0.006 | 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 | 0.015 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".