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Record W2108954761 · doi:10.1123/jsm.17.2.116

Cohesion in Volunteer Sport Executive Committees

2003· article· en· W2108954761 on OpenAlexaff
Alison Doherty, Albert V. Carron

Bibliographic record

VenueJournal of Sport Management · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsWestern University
Fundersnot available
KeywordsGroup cohesivenessCohesion (chemistry)PsychologyPerceptionAmateurExecutive committeeSocial psychologyPublic relationsVolunteerApplied psychologyManagementPolitical science

Abstract

fetched live from OpenAlex

Understanding the experiences of volunteers in amateur sport organizations is critical to their effective management of these nonprofit organizations. The purpose of this study was to explore cohesion in volunteer sport executive committees. Members (n = 117) of sport executive committees or boards completed a questionnaire that assessed perceptions of cohesion, individual satisfaction, effort, intent to quit, committee effectiveness, and a variety of individual (gender, committee, role, tenure) and organizational (committee, size, gender composition, frequency and length of meetings) variables. Task cohesion was found to be stronger than social cohesion. Only committee size was found to be associated with perceptions of cohesiveness; members of smaller committees perceived less social cohesion than members of medium and larger committees. Task and social cohesion predicted volunteer satisfaction and perceived committee effectiveness, while volunteer effort and intent to remain with the committee were predicted by task cohesion. The results are discussed in terms of their implication for theory and practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.287
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations116
Published2003
Admission routes1
Has abstractyes

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