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Record W3081596043 · doi:10.26443/firr.v10i1.29

Sport Diplomacy: Sport’s Impact as a Form of Soft Power on Peacebuilding and Nation-Building in the Israeli-Palestinian Conflict

2020· article· en· W3081596043 on OpenAlexaffvenue
Ender McDuff

Bibliographic record

VenueFlux International Relations Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsMcGill University
Fundersnot available
KeywordsNegotiationDiplomacyPeacebuildingSoft powerContext (archaeology)Political sciencePower (physics)InsurgencyPoliticsPolitical economyConflict resolutionLawSociologyHistory

Abstract

fetched live from OpenAlex

Since the founding of the first Israeli and Palestinian soccer clubs in 1906 and 1908, respectively, sport has played an intimate role in the Israeli-Palestinian conflict. Whether as a training ground for counter-insurgency operations or an extension of the nation’s foreign policy apparatus, sport has been utilized by both parties as a tool for peacebuilding and nation-building. The purpose of this article is to examine whether sport, through what is termed sport diplomacy, can help establish the conditions necessary for successful peace negotiations in the Israeli-Palestinian conflict. To this effect, the paper adopts the analytical lens of sport as a form of soft power. Following this framework, the paper considers how sport diplomacy operates as a tool for image-building, constructing a platform for dialogue, trust building, and as a catalyst for reconciliation in the context of the Israeli-Palestinian conflict. The article concludes that sport can indeed help establish the conditions needed for successful peace negotiations; however, sport should not yet be employed as a path to reconciliation until such time as a political peace is firmly established.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.397
Teacher spread0.339 · 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.

Study designNot applicable
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

Citations1
Published2020
Admission routes2
Has abstractyes

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