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Record W3134282139 · doi:10.1177/0010414021997498

Team and Nation: Sports, Nationalism, and Attitudes Toward Refugees

2021· article· en· W3134282139 on OpenAlex

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.

Bibliographic record

VenueComparative Political Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of British Columbia
FundersAgence Nationale de la RechercheMassachusetts Institute of TechnologyPrinceton University
KeywordsPrideRefugeeNationalismEthnic groupPolitical scienceNational identityCognitive reframingSocial psychologySuperordinate goalsPublic relationsSociologyPoliticsPsychologyLaw

Abstract

fetched live from OpenAlex

How do major national events influence attitudes toward non-nationals? Recent research suggests that national sports team wins help foster national pride, weaken ethnic attachments, and build trust among conational out-group members. This paper asks a related question: By heightening nationalism, do these victories also affect attitudes toward foreign out-groups, specifically refugees? We examine this question using the 2019 Africa Cup football match between Kenya and Tanzania, which Kenya narrowly won, coupled with an online survey experiment conducted with a panel of 2,647 respondents recruited through Facebook. We find that winning increases national pride and preferences for resource allocation toward conationals, but it also leads to negative views of refugees’ contribution to the country’s diversity. However, we present experimental evidence that reframing national sports victories as a product of cooperation among diverse players and highlighting shared superordinate identities can offset these views and help foster positive attitudes toward refugees.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.477

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.223
GPT teacher head0.492
Teacher spread0.269 · 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