A relational autonomy argument against public funding for non-invasive prenatal testing (NIPT): the routinization of NIPT and the geneticization of pregnancy and reproduction
Bibliographic record
Abstract
Non-invasive Prenatal Testing (NIPT) is a genetic test that analyzes cell-free fetal DNA (cfDNA) in maternal blood as early as ten weeks into pregnancy. It is a reasonably accurate screening tool for detecting chromosomal conditions such as Patau, Edwards, and Down syndromes, caused by Trisomy 13, 18, and 21, respectively. Although disability rights advocates have strongly opposed public funding for NIPT, arguing that government endorsement of the test sends a discriminatory message, implying that a life without a disability is more valuable than a life with a disability, several Canadian provinces and territories offer public funding for NIPT, subject to specific eligibility criteria for pregnant individuals. Proponents of funded NIPT argue that funding enhances reproductive autonomy by enabling pregnant individuals to make informed decisions regarding continuing or terminating a pregnancy. While this dissertation challenges this conventional autonomy argument - that claims that funded NIPT expands pregnant people’s reproductive choices to terminate or continue pregnancy - put forth by proponents of funded NIPT, it instead proposes an argument against funded NIPT based on the concept of relational autonomy. A relational perspective of autonomy, advocated by feminist bioethicists, focuses on adverse social and structural conditions that can undermine women’s free reproductive choices. This dissertation promotes a relational concept of autonomy and argues that public funding for NIPT can undermine reproductive autonomy by routinizing its use in prenatal care and normalizing genetic testing in prenatal care that might influence a pregnant person to accept NIPT without fully considering its implications for their life. If NIPT becomes a standard genetic test in prenatal care, it may become difficult for many pregnant individuals to decline the test. Moreover, providing public funding for NIPT can encourage the widespread use of this test, subtly oppressing individuals to undergo testing and potentially terminate pregnancies based on results, ultimately undermining their reproductive autonomy. To cultivate a more inclusive and supportive environment within Canadian prenatal care, governments must revise their NIPT funding policy to disrupt structural barriers to pregnant people’s reproductive autonomy. The dissertation concludes with recommendations to: enhance informed decision-making, address the impacts of technological advancements, consider caseby- case public funding, and foster inclusivity for people with disabilities. These steps can create a more inclusive prenatal care landscape that upholds reproductive autonomy in a relational sense.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.038 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".