MétaCan
Menu
Back to cohort

Friend or Foe? A World View of Community-Police Relations in Gauteng Townships, 1947-77

2003· article· en· W1518475567 on OpenAlexvenueaboutno aff
Gary Kynoch

Bibliographic record

VenueCanadian Journal of African Studies / Revue canadienne des études africaines · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les relations entre police et communauté dans les townships (municipalités) d’Afrique du sud sont orageuses depuis des décennies. On suppose depuis longtemps que l’hostilité des Africains des villes envers la police remonte au moins au début de la période de l’apartheid. Cette étude de reportages effectués par un journal africain important sur le maintien de l’ordre et le crime dans la région de Johannesburg indique que la relation était beaucoup plus complexe jusqu’à la révolte de Soweto en 1976. Pour de nombreux résidents des townships, la peur du crime supplantait leur ressentiment à l’égard de la police qui imposait la législation de l’apartheid, et avant 1976, ces gens recommandaient de coopérer avec la police pour réduire les niveaux de criminalité. Les gendarmes noirs, en particulier, recevaient un appui important et les résidents faisaient campagne pour obtenir une augmentation et du nombre de gendarmes africains et de leurs responsabilités à la tête des unités de commandement. Les violences policières pendant les soulèvements, qui se sont essentiellement exercées contre les étudiants, ont représenté un moment décisif dans la détérioration des relations entre communauté et police, détérioration qui s’est poursuivie pendant la violence politisée des années 1980 et 1990.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.964

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0160.014
Scholarly communication0.0080.008
Open science0.0010.003
Research integrity0.0030.003
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 head0.082
GPT teacher head0.289
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations15
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of African Studies / Revue canadienne des études africainesSame topicSouth African History and CultureFrench-language works237,207