MétaCan
Menu
Back to cohort

On The Green: Consumer Perceptions of Returning to Golf Spectatorship Amid the Covid-19 Pandemic

2022· article· en· W4296473223 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEvent Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPandemicAttendancePerceptionCoronavirus disease 2019 (COVID-19)Event (particle physics)PsychologyMarketingTourism2019-20 coronavirus outbreakRevenueBusinessAdvertisingPublic relationsPolitical scienceMedicineEconomicsEconomic growthDiseaseFinance

Abstract

fetched live from OpenAlex

Throughout the COVID-19 pandemic, the sport industry has contended with stoppages of play and interrupted revenue streams. With sport beginning to "return to normal," there is uncertainty about the safe return of spectatorship and how live-event attendees perceive safety and precautionary measures amid a serious health emergency. The purpose of this study was to assess golf consumers' perceptions of following COVID-19 preventative measures at a small-scale professional golf event in Canada, and how these perceptions may influence their future event attendance. The results from a multiple linear regression analysis indicated that perceived benefits of COVID-19 vaccination and self-efficacy of following preventative measures significantly and positively influenced golf spectator's consideration of attending an event where these measures are enforced, while the perceived barriers of mask wearing significantly and negatively influenced attendance consideration. This has several practical implications for event management practitioners planning and hosting an event amid the COVID-19 pandemic.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.075
GPT teacher head0.357
Teacher spread0.282 · 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