Terence Keel. Divine Variations: How Christian Thought Became Racial Science.
Bibliographic record
Abstract
It is widely appreciated that current struggles over race and racism are crucially shaped by the history of racism. In his book Divine Variations: How Christian Thought Became Racial Science, Terence Keel masterfully demonstrates how this is true not only with respect to the legacy of historical racism on ongoing racialized inequality; it is also manifest in how modern scientific approaches to race have been informed by religious conceptions that scientists have often understood themselves to be leaving behind. Keel is by no means the first scholar to demonstrate how modern racial science has been informed by Christian religious conceptions of distinct branches of humanity. But he adds considerable depth and specificity to our understanding of how modern ideas about distinct human races involve what he calls the “modern scientific appropriation of Christian supersessionism” (10). Through examinations of well-chosen race scientists and historical moments, Keel illuminates “Christian thinking about a creator God, Judaism, nature, time, and human ancestry that influenced scientific ideas about race” (7).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".