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Record W4411134534 · doi:10.1080/16138171.2025.2509052

Collective identities of VSCs: influencing factors and impact

2025· article· en· W4411134534 on OpenAlexaff
Resie Hoeijmakers

Bibliographic record

VenueEuropean Journal for Sport and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsSociologySocial psychologyPsychology

Abstract

fetched live from OpenAlex

This paper explores the positive effects and factors that shape collective identities within voluntary sport clubs (VSCs). As the role and development of collective identities in VSCs remain poorly understood, Classic Institutional Theory is combined with Social Identity Theory to identify the micro- and organisational-level factors that shape these identities. A multiple case study is performed among four Dutch voluntary tennis clubs. Results show significant positive relationships between members’ level of organisational identification and three indices of member involvement (loyalty, volunteering and positive WOM). Given that VSCs rely heavily on member involvement for their functioning, this suggests that both providing club goods that align with members’ interests and fostering a collective identity are crucial for their long-term survival. Furthermore, to understand how collective identities are fostered, this study examined which social groups are key in shaping collective identities within VSCs and identifies the organisational factors that trigger organisational identification processes. Results show that embeddedness in social relationships and various social groups within VSCs, shape collective identities and spur organisational identification among members. Governmental policy aimed at strengthening VSCs should therefore focus on imbuing VSCs with identity cues and stimulating the formation of social relationships between members.

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 score0.133
Threshold uncertainty score0.772

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 studies0.0010.000
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 head0.017
GPT teacher head0.310
Teacher spread0.293 · 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
Published2025
Admission routes1
Has abstractyes

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