Bibliographic record
Abstract
This thesis critically examines the ethical implications of using Pre-Implantation Genetic Diagnosis (PGD) to avoid the birth of intersex children, challenging the arguments presented by Robert Sparrow in "Gender Eugenics? The Ethics of PGD for Intersex Conditions" (2013). Sparrow defends the use of PGD for intersex avoidance to promote the future child's well-being. Still, this work contends that such practices are ethically indefensible and perpetuate harmful societal narratives. First, it employs the Expressivist Critique to illustrate how reproductive decisions in the context of intersex avoidance perpetuate the devaluation of intersex lives, challenging the notion of ethical neutrality in such practices. Second, exploring intersex avoidance through the lens of Donna Haraway's Cyborg Feminism, the thesis highlights the cultural and psychological implications of rejecting intersex identities and reinforcing binary gender norms. Third, it examines parental ethics, advocating for an approach to parenting that embraces openness while emphasizing the ethical dimensions of reproductive decisions. The thesis ultimately calls for a more inclusive understanding of intersex variations, urging a re-evaluation of societal and ethical frameworks to foster a diverse and accepting community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".