The Quiet Progress of the New Eugenics. Ending the Lives of Persons With Intellectual and Developmental Disabilities for Reasons of Presumed Poor Quality of Life
Bibliographic record
Abstract
Abstract This paper considers recent developments in terminating human life affected by intellectual and developmental disability. It brings these developments together under the heading of a progressing eugenics. It argues that the acts under discussion are eugenic with regard to their moral justification, even if not in their intention. Terminating human life in contemporary society is aiming at the alleviation of suffering, not the enhancement of the human gene pool. Three distinct cases are traced in the literature: ending the lives of severely disabled prematurely born infants, terminating pregnancies after positive outcomes of genetic screening and testing, and ending the lives of persons with IDD by means of euthanasia. It is shown from the literature that in each of these cases the justifying reason is the prospective judgment of a ‘poor’ quality of life, which ties these acts to the justification of terminating human life within the history of eugenics. The pervasive judgment of poor quality of life is criticized as ignoring alternative views, most of all the views of persons and families directly implicated who do not consider living with IDD identical with a life full of suffering.
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".