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Record W4378071217 · doi:10.31542/cb.v5i1.2521

Cross-Border Tensions Affecting Sports

2023· article· en· W4378071217 on OpenAlex
Dua Nauman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCrossing Borders Student Reflections on Global Social Issues · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsMacEwan University
Fundersnot available
KeywordsCricketPopulationPolitical scienceRajaPoliticsSociologyPublic relationsPolitical economyLaw

Abstract

fetched live from OpenAlex


 
 
 This study aimed to explore cross-border tensions affecting sports and how people reacted to the decision made in the wake of those tensions. Fifty Twitter comments were sampled using a purposive method to gain knowledge about the themes in reactions to bold decisions made by Ramiz Raja. Results revealed 11 main themes. The literature suggests that disputes are brought up by politicians, which reflects the general population. The results show that the public does not hold the same views as the politicians, and people are more accepting of moving past conflicts. People are very protective of cricket in both nations. Current events have shown that despite politicians working hard to keep nations apart, the people do not completely agree.
 
 

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0140.001
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.557
Teacher spread0.491 · 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