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Record W2113786150 · doi:10.5334/sta.ft

Violence and Democracy in Khayelitsha, Governing Crime through the ‘Community’

2015· article· en· W2113786150 on OpenAlexvenueno aff
Gail Super

Bibliographic record

VenueStability International Journal of Security and Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyCriminologyPolitical scienceSociologyLawPolitics

Abstract

fetched live from OpenAlex

Waving placards that read “Sonele zizikoli, sanele yicrime (we have had enough of crime and thugs),” more than 60 angry residents protested outside the Khayelitsha Police Station on Tuesday. [ . . . ] Residents’ leader Unathi Mabengwana said: “Given the high crime rate in our area, we are of the view that whatever cops do to fight crime here is not enough. We demand that cops should be more harsh when dealing with criminals.” Greg Wagner, spokesman for community safety department said [Member of the Executive Council] Dan Plato will meet with the Western Cape police commissioner, General Arno Lamoer, to discuss the issue next week. Wagner said the meeting would also be a follow up on the recent vigilante attacks, in which three alleged crime suspects were burnt to death at Enkanini squatter camp (Mnyakama 2012).

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)0.001
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: none
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0210.016
Scholarly communication0.0060.002
Open science0.0000.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.079
GPT teacher head0.354
Teacher spread0.276 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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