MétaCan
Menu
Back to cohort

Sport Mega-Event Volunteers' Motivations and Postevent Intention to Volunteer: The Sydney World Masters Games, 2009

2015· article· en· W2215448492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvent Management · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsEvent (particle physics)Mega-Social psychologySurvey data collectionPsychologySociology

Abstract

fetched live from OpenAlex

Investment in mega-sport events is frequently justified on the basis that there are infrastructure and social legacies that remain after the event. This research explores the claims of a social legacy through a pre- and post-Games survey of volunteers at the Sydney world Masters Games 2009 (SwMG). Through online surveys the research explores pre-and post-volunteer motivations, postevent volunteering intentions before the Games and actual volunteer behavior after the Games. The pre-Games survey supports previous research that a desire to be involved in the event motivates people to volunteer. however, the postevent expression of motivations shifted to a more altruistic focus. The postevent volunteering intentions as indicated in the preevent survey would support the claim of a social legacy; however, this was not supported by the postevent measures of volunteering levels. The use of a pre- and postevent survey has highlighted that the timing of measures of motivations can influence responses and one may not depend on preevent intentions as an indicator of postevent behaviors.

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.301
Teacher spread0.273 · 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