STATISTICAL CRITICISM AND THE EMINENT MAN IN FRANCIS GALTON'S<i>HEREDITARY GENIUS</i>
Bibliographic record
Abstract
Inspired by the power and influencethat Charles Darwin attributed to heredity inOn the Origin of Species(1859), Francis Galton developed a program of eugenics that he believed could shape Britain's progress as a nation by managing the evolutionary development of the British race. InInquiries into Human Faculty and its Development(1883), Galton summarizes this aim as “to learn how far history may have shown the practicability of supplanting inefficient human stock by better strains, and to consider whether it might not be our duty to do so by such efforts as may be reasonable, thus exerting ourselves to further the ends of evolution more rapidly and with less distress than if events were left to their own course” (1–2). While this project, Galton's life's work, was largely a process of analysis and the development of dictates that could be put in place to shape the reproduction of the nation, it was also a project of imagination; not only was Galton himself imagining a different future for Britain, but in promoting his program, he appealed to the imaginations of his readers in an attempt to get them to share his vision.
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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 | 0.071 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.060 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.009 | 0.018 |
| 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".