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Record W2568037931

All for one? Collective responsibility and psychological climate

2015· article· en· W2568037931 on OpenAlexaff
Kathleen Wilson, Kevin S. Spink

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2015
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCollective responsibilityMoral responsibilitySocial psychologyPsychologyMultivariate analysis of variancePerceptionSocial responsibilityPolitical sciencePublic relationsLaw
DOInot available

Abstract

fetched live from OpenAlex

While attributing responsibility for an outcome has a long history in psychology (Heider, 1958), it has received much less attention in sport. This is surprising given that teams are typically lauded for their 'all for one mentality', yet, games are often ostensibly decided by the play of one or a subgroup of players. Further, if the perception is that all members are collectively responsible for a losing outcome, then what does that say about team climate? This study explored whether perceptions of differing levels of responsibility (individual or collective) by members would be associated with different perceptions of psychological climate (PC) within a sport team. Curlers (N=66) completed online measures of PC (Spink et al., 2012) and collective responsibility (designed for this study) near the end of their season. For the analysis, individuals were split into two responsibility groups: 1) those who reported that individuals were more responsible for losses (individual responsibility, n=29), and, 2) those who reported that the team was more responsible for losses (collective responsibility, n=37). A MANOVA was performed with responsibility as the IV (individual vs collective responsibility) and the PC subscales as the DVs. Results revealed that PC differed across the levels of responsibility, F(4,61)=2.616, p=.044, etap2=.15. Post hoc analysis revealed that self-expression was the PC subscale that significantly differed between conditions (F(1, 64) = 4.61, p=.036). Those who perceived that it was primarily the team (versus individuals) who was collectively responsible for the loss reported being more able to express themselves around the team.

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)0.002
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 score0.251
Threshold uncertainty score0.373

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 head0.166
GPT teacher head0.441
Teacher spread0.275 · 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
Published2015
Admission routes1
Has abstractyes

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