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Record W2808845100 · doi:10.3167/hrrh.2018.440109

The “Moral Effect” of Legalized Lawlessness

2018· article· en· W2808845100 on OpenAlexvenueno aff
Caroline Elkins

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLawlessnessEmpireAuthoritarianismColonialismLiberalismLawIdeologyCoercion (linguistics)British EmpirePolitical scienceSociologyCriminologyHistoryPolitical economyDemocracyPhilosophyPolitics

Abstract

fetched live from OpenAlex

From 1930s Palestine to Kenya in the years following World War II, systematized violence shaped and defined much of Britain’s twentieth-century empire. Liberal authoritarianism, and with it the “moral effect” that coercion had upon colonial subjects, gave rise to the systematic use of violence against colonial subjects. The ideological roots of these tactics can be located in the twinned birth of liberalism and imperialism, together with metropolitan responses to imperial events in the mid-nineteenth century. Despite copious amounts of empirical evidence documenting the evolution of liberal authoritarianism, and the creation and deployment of legalized lawlessness throughout the British Empire, Steven Pinker either ignores this evidence, or implicitly denies its validity. In reframing Britain’s civilizing mission, and challenging liberalism’s obfuscating abilities, this article critiques not only the British government’s repeated denials of systematized violence in its empire, but also Pinker’s reinforcement of the myths of British imperial benevolence.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.127
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.061
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.046
GPT teacher head0.292
Teacher spread0.245 · 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
GenreEmpirical

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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