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Record W2783742610

Silent Accomplices & Victims in Disguise

2017· book· no· W2783742610 on OpenAlexaboutno aff
Dominik Kaiserseder

Bibliographic record

VenueAV Akademikerverlag eBooks · 2017
Typebook
Languageno
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsCriminologyHistoryViolent crimeBiographyQuarter (Canadian coin)SociologyGender studiesArt history
DOInot available

Abstract

fetched live from OpenAlex

Almost a quarter of a century after the abolition of apartheid, violent crime and fear thereof continues to afflict South Africa. Until well into the 20th century, the country’s literary canon primarily dwelled on presentations of inter-racial violence, suggesting that whites are the sole targets of violence inflicted by ‘evil savages’. In the past seventy years, however, this notion was challenged by writers who increasingly attributed ‘native crime’ to structural (institutionalized) violence and depicted native lawbreakers as victims in disguise. Based on five literary texts, including Paton’s novel 'Cry, The Beloved Country', Mphahlele’s autobiography 'Down Second Avenue', Matthews’ short story “The Park”, Fugard’s play 'My Children! My Africa!' and Coetzee’s novel 'Disgrace', this book aims at disclosing the origin of violent crime in present-day South Africa. An initial outline of Galtung’s ‘violence triangle’, which discusses three forms of violence (direct, structural and cultural violence), serves as a theoretical foundation for the literary analysis, on the basis of which the causality of crime shall be explored.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.014
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.040
GPT teacher head0.298
Teacher spread0.258 · 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
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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