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Evidence of a Social Legacy from Volunteering at the Sochi 2014 Olympic and Paralympic Winter Games

2022· article· en· W4285199525 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 · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsEvent (particle physics)TourismPublic relationsSociologyAdvertisingPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Mega-sport events, like Olympic and Paralympic Games, typically promise host communities that beneficial legacies will remain beyond the life of the event; however, there is little postevent research supporting these claims. Conducted 3 years after the Sochi 2014 Olympic and Paralympic Winter Games, this research is one of few to explore the social legacy of volunteerism following an Olympic and Paralympic Games. A previously developed anonymous online survey was distributed via the event's 26 volunteer centers. Analysis included principal components analysis and independent samples t tests. The results demonstrate that social legacies can be achieved, albeit at a level lower than may be indicated by surveys conducted at the time of the event. By being strategic in their recruitment and training of volunteers, future mega-sport event organizers may be more effective in achieving social legacies, in sport, events, and tourism, that add to a host community's social and human capitals.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.999

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 science0.0000.001
Research integrity0.0000.000
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 head0.025
GPT teacher head0.300
Teacher spread0.274 · 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