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Record W3165221482 · doi:10.1163/17087384-12340080

Architecture of Denial: Imperial Violence, the Construction of Law and Historical Knowledge during the Mau Mau Uprising, 1952–1960

2021· article· en· W3165221482 on OpenAlexvenueno aff
Juliana Appiah, Roland Mireku Yeboah, Akosua Asah-Asante

Bibliographic record

VenueAfrican Journal of Legal Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
FundersUniversity of GhanaYale University
KeywordsColonialismTortureLawDenialKenyaGovernment (linguistics)Human rightsPolitical scienceSociologyHistory

Abstract

fetched live from OpenAlex

Abstract In 2013, the UK government settled a class action suit, which alleged that the British Colonial Government had subjected Kenyans to detainment, ill treatment and torture during the 1952–1960 ‘Kenya Emergency’. During the trial proceedings, the efforts of three expert historical witnesses for the prosecution – Caroline Elkins, David Anderson and Huw Bennett – led to the discovery of a cache of over 8,000 historical files from 36 former British colonies. The material contained within these documents suggested not only that Britain was aware of pervasive human rights abuses occurring throughout Kenya during the Emergency, but that the use of such violence was in fact endorsed and systematically regulated at the highest levels of the colonial administration. Drawing on Foucault’s conception of historical archives as ‘systems of discursivity’, and making use of the testimonies of the three experts, this article explores how the British Colonial Administration was able to dominate the discursive space surrounding Kenyan law and Mau Mau identity, allowing it both to justify the implementation of systemic violence throughout the Emergency, and to evade legal responsibility for these abuses at the time, and for decades afterward.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.233
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2021
Admission routes1
Has abstractyes

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