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Large-scale sport events and well-being: Exploring residents’ pre-event perspectives

2025· article· en· W4417139008 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 · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsBrock University
Fundersnot available
KeywordsStakeholderEvent (particle physics)Host (biology)Meaning (existential)Key (lock)Stakeholder engagementFocus group

Abstract

fetched live from OpenAlex

Large-Scale Sport Events (LSSE) are increasingly contested as host cities balance the benefits and costs of these events. Residents are a stakeholder group heavily impacted by LSSE given their rootedness in the host city over the event lifecycle spanning: bid submission, awarding of host rights, pre-event planning, event delivery, post-event shutdown and beyond. Yet, limited focus has been placed on understanding residents' perceptions of LSSE impacts in the pre-event period. Twenty-seven semi-structured interviews, guided by Seligman’s (2011) PERMA framework, were conducted with Australian residents in 2023 FIFA Women’s World Cup host cities. Findings demonstrated how four PERMA domains (positive emotions, relationships, meaning and accomplishment) were activated. Findings advance understanding of how LSSE can positively impact residents in a phase of the event lifecycle when event organisers and host governments are often not yet actively engaging with this key stakeholder group. Key theoretical and practical implications are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.924

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 head0.018
GPT teacher head0.314
Teacher spread0.296 · 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