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Record W4225254137 · doi:10.1123/jsep.2021-0136

Attitudes of Sport Fans Toward the Electronic Sign-Stealing Scandal in Major League Baseball: Differing Associations With Perfectionism and Excellencism

2022· article· en· W4225254137 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

VenueJournal of Sport and Exercise Psychology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsUniversity of ManitobaUniversity of Ottawa
Fundersnot available
KeywordsCheatingPsychologySign (mathematics)Perfectionism (psychology)Social psychologyLeaguePerfectionLoyaltyExcellenceTheology

Abstract

fetched live from OpenAlex

The winners of the 2017 World Series were found guilty of illegally using electronic devices to steal the signs of their opponents. Many but not all sport fans negatively reacted to this cheating incident. We relied on the model of excellencism and perfectionism to determine if perfection strivers are less unfavorable toward electronic sign stealing (cheating) compared with excellence strivers. Sport fans (N = 321) completed a measure of excellencism and perfectionism. We used three different approaches to measure attitudes toward electronic sign stealing in baseball. Results of a multivariate multiple regression showed that sport fans who are perfection strivers held more favorable attitudes toward electronic sign stealing compared with excellence strivers. Perfection strivers also reported higher moral disengagement and winning-at-all-cost mentality. These findings are insightful because they indicate that perfectionistic standards significantly relate to sport cheating-related attitudes once we separate excellencism from perfectionism.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.018
GPT teacher head0.303
Teacher spread0.285 · 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