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Record W2808060414 · doi:10.1123/iscj.2017-0054

Correcting Player Mistakes: Effects of Coach and Player Social Influence on Increasing Player Intention to Intervene with Teammates

2018· article· en· W2808060414 on OpenAlexaff
Kevin S. Spink, Kayla B Fesser

Bibliographic record

VenueInternational Sport Coaching Journal · 2018
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMistakePsychologyNorm (philosophy)Social psychologyTeam sportApplied psychologyAthletesPolitical science

Abstract

fetched live from OpenAlex

Correcting mistakes is a key component in sport performance. Typically, the coach is tasked with providing this feedback. While teammates could serve this role, it is not the norm for teammates to provide this feedback (Goldsmith & Fitch, 1997). The purpose of the present study was to examine the effect of coach and player sources of social influence on increasing player intention to intervene with teammates following a technical mistake. Adult soccer players ( N = 170) read one of five hypothetical soccer team vignettes where the description differed in the levels of coach and player social influence about intervening with teammates. Participants rated their intention to intervene with teammates who made a technical mistake during a game. ANCOVA results indicated that the overall model was significant ( p < .002). Post hoc analyses revealed that intention to intervene was higher when teams were described as having a coach that encouraged players to intervene and the team norm was for players to intervene. However, this was not the case when coach and teammate social influences were at cross purposes. This provides initial support that aligned social influences from the coach and players increase soccer players’ intentions to intervene when their teammates make technical mistakes.

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)0.000
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 score0.025
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.013
GPT teacher head0.302
Teacher spread0.289 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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