Bibliographic record
Abstract
About a decade ago, President William Clinton said that the next half century will be the age of biology, and, that the engine of that age is genetics.Partly because of the Human Genome Project, scientists have been producing a torrent of information and claims about the role of genes in human disease, capacities, and behaviour.The new knowledge is bringing about a revolution in the diagnosis of diseases and disorders.It is also predicted to yield a powerful arsenal of therapies and cures-and possibly an ability to improve people genetically.According to some, it may also fulfil the longstanding dream of the eugenics movement, which flourished during the first-third or so of the last century.In a number of ways, the eugenics movement trampled on human rights as we understand them.It has no more powerful association than with the Nazis.In Germany during the Hitler years, the eugenics movement prompted the sterilisation of several hundred thousand people and helped lead to anti-Semitic programmes of euthanasia and ultimately, of course, to the death camps.But in fact after the turn of the century, eugenics movements, including demands for sterilisation of the unfit, blossomed in the United States, Canada, Britain, and Scandinavia, not to mention elsewhere in Continental Europe and parts of Latin America and Asia.Eugenics was thus not unique to the Nazis.It could-and did-happen everywhere.
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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".