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Record W6998753648

Arts and Sports in South Africa: Alternative Post-conflict Peacebuilding Tools for Positive Peace

2016· article· en· W6998753648 on OpenAlexfundno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsThe artsCohesion (chemistry)InequalityCommunity cohesionGovernment (linguistics)RacismPoverty
DOInot available

Abstract

fetched live from OpenAlex

This paper explores the effectiveness of arts and sports programs in the construction of positive peace in South Africa after Apartheid. It does so by collecting information on different arts and sports programs carried out by government and non-government organizations which take place in different cities and townships located in three of the main provinces of the country: Gauteng, Western Cape and KwaZulu Natal. I documented the impact of arts and sports programs in the construction of positive peace. To measure the contribution of these programs I used social cohesion as an indicator of peacebuilding. I argue that although arts and sports programs are effective in promoting social cohesion within communities of the same race, they fail to encourage social cohesion among communities of different races. The existing economic divide of social classes in South Africa contributes to the lack of social integration between black and white South Africans. Hence, in order to promote social cohesion at a national level, it is imperative to breach the economic inequality gap which is entrenched in the existent racial divide from the Apartheid era.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.978

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.290
Teacher spread0.254 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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