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Record W1974293891 · doi:10.1080/19407960903204356

The volunteer legacy of a major sport event

2009· article· en· W1974293891 on OpenAlexaffabout
Alison Doherty

Bibliographic record

VenueJournal of Policy Research in Tourism Leisure and Events · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsWestern University
Fundersnot available
KeywordsEvent (particle physics)PsychologySocial psychologyTask (project management)Action (physics)Applied psychologyManagement

Abstract

fetched live from OpenAlex

The purpose of this study was to understand the volunteer legacy of a major sport event and identify aspects of the event that shaped future voluntary action in the host community. Social exchange theory framed the examination of volunteers’ positive and negative experiences with the event as a predictor of future behavioral intentions. A total of 1098 volunteers involved with the 2001 Canada Summer Games completed a post‐event survey. In general, planning volunteers’ future volunteering was particularly influenced by experienced costs of the event (task overload, personal inconvenience), although contributing to the community and a positive life experience were also predictive of their future involvement. In contrast, on‐site volunteers’ future volunteering was more influenced by experienced benefits of the event, including social enrichment, community contribution, and a positive life experience. However, personal inconvenience and task underload were also predictive of their future involvement. The findings have implications for event policy and management that should acknowledge the potential for major sport events to engender a legacy of volunteering.

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)0.008
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
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)0.0020.000

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 head0.053
GPT teacher head0.442
Teacher spread0.388 · 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

Citations193
Published2009
Admission routes2
Has abstractyes

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