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Record W2809555385 · doi:10.3167/hrrh.2018.440112

The Inner Demons of The Better Angels of Our Nature

2018· article· en· W2809555385 on OpenAlexvenueno aff
Daniel Lord Smail

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipDepictionPeriod (music)HistorySociologyEpistemologyAestheticsPsychologyCriminologyLiteratureArtLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

The Better Angels of Our Nature makes a bold contribution to the deep history of human violence. By laying out a framework for understanding this history, Steven Pinker has provided an important point of departure for all future scholarship in this area. Pinker’s depiction of violence in medieval Europe, however, includes serious misrepresentations of the historical reality of this period; his handling of the scholarship on medieval Europe raises doubts about his treatment of other periods. This article also offers a brief review of recent psychological literature that suggests that subjective well-being is historically invariant. In light of this review, I argue that Better Angels is best understood not as a work of history but as a study in moral and historical theology, and recommend that the history of violence should feature the cognitive experiences of victims rather than aggressors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.051
Scholarly communication0.0080.011
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.030
GPT teacher head0.374
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations13
Published2018
Admission routes1
Has abstractyes

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