Bibliographic record
Abstract
What would bring a physician to conclude that sterilization is appropriate treatment for the mentally ill and mentally handicapped? Using archival sources, Ian Robert Dowbiggin documents the involvement of both American and Canadian psychiatrists in the eugenics movement of the early twentieth century. He explains why professional men and women committed to helping those less fortunate than themselves arrived at such morally and intellectually dubious conclusions. Psychiatrists at the end of the nineteenth century felt professionally vulnerable, Dowbiggin explains, because they were under intense pressure from state and provincial governments and from other physicians to reform their specialty. Eugenic ideas, which dominated public health policy making, seemed the best vehicle for catching up with the progress of science. Among the prominent psychiatrist-eugenicists Dowbiggin considers are G. Alder Blumer, Charles Kirk Clarke, Thomas Salmon, Clare Hincks, and William Partlow. Tracing psychiatric support for eugenics throughout the interwar years, Dowbiggin pays special attention to the role of psychiatrists in the fierce debates about immigration policy. His examination of psychiatry's unfortunate flirtation with eugenics elucidates how professional groups come to think and act along common lines within specific historical contexts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".