The Darker Angels of Our Nature: Refuting the Pinker Theory of History and Violence, ed. Philip Dwyer and Mark Micale
Bibliographic record
Abstract
Assiduous readers of the EHR might recall my long review article on recent work in early modern violence that focused on Steven Pinker’s landmark survey The Better Angels of Our Nature (2011), followed by a discussion of recent work by specialists of criminal history of the early modern era (ante, cxxviii [2013], pp. 367–400). My critique of his work complained of ‘page after page of wild exaggeration, hyperbole, junk statistics and reference to fiction as if it were fact’. This legitimate annoyance was, I thought, largely salvaged by his presentation of work on the underpinnings of our moral bearings that trigger so much violence. That work does not differ substantially from Robert Sapolsky’s big book from 2017, Behave. Pinker confers credit for the drastic decline of violence in the West on Enlightenment ideas. His chronology is off by a full century, however. Leviathan claimed a monopoly over violence, and people had good reasons to trust Big Government to protect their lives and property and to punish wrongdoers.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".