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Record W4398781822 · doi:10.1080/02699931.2024.2358381

The effects of nonverbal pride and skill on judgements of victory and social influence: a boxing study

2024· article· en· W4398781822 on OpenAlexaff
Jason P. Martens, Lucy Doytchinova

Bibliographic record

VenueCognition & Emotion · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCapilano University
Fundersnot available
KeywordsPrideVictoryPsychologyNonverbal communicationPerceptionSocial psychologyContext (archaeology)Developmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Displaying nonverbal pride after a boxing match leads to judgements of success. However, it is not clear the extent to which this effect generalises nor whether it can override competing information. An experimental design had 214 participants watch two boxing clips that were manipulated so that one was evenly matched and the other had a fighter with an advantage (i.e. demonstrating more skill). Nonverbal behaviour at the completion of the fight varied between fighters (pride versus neutral). When the fight was evenly matched, the fighters displaying nonverbal pride were judged as winning the fight, but the fighter did not garner increased social influence. In contrast, when fighters demonstrated superior skill, the more skilled fighters who displayed neutral postures rather than the less-skilled ones displaying pride were judged as winning the fight, and the skilled fighters garnered increased social influence. These results suggest that in a boxing context, a pride bias works in evenly matched scenarios, but when differences in skill are more clearly present, a skill bias is more pronounced and leads to more social influence. Furthermore, perceptions of skill were associated with judgments of victory across stimuli, suggesting the importance of skill perceptions in such judgments.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.224

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 communication0.0000.000
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 head0.012
GPT teacher head0.326
Teacher spread0.314 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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