The Intersection of Ableism, Domestic Colonialism and Statistics in Britain from Bentham to Galton
Bibliographic record
Abstract
Statistics, ableism and domestic colonialism were inextricably intertwined in Britain over the long nineteenth century, based on both engineering people deemed to be “backward” and improving “waste” land, which together were used to justify farm colonies for the disabled, bookended by two key moments. The first is Sir John Sinclair's introduction of descriptive statistics into the English language in order to provide a foundation for domestic colonization which, as the founding president of the British Board of Agriculture and Internal Improvement, he promoted. He also enlisted Jeremy Bentham, who published his own domestic colonization plan (massive pauper panopticons on waste land) rooted in the statistics of his pauper population table. The second key moment occurs at the beginning of the twentieth century, when Sir Francis Galton develops key statistical arithmetic methods as the foundation for eugenics and his defense of compulsory segregation of the mentally disabled into domestic farm colonies.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".