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Decoding Sustainability Signals: Spectator Perspectives at the 2022 European Championships

2024· article· en· W4404465275 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 · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsSustainabilityTourismDecoding methodsPsychologyAdvertisingSociologyPolitical scienceAestheticsArtBusinessComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

In this study, we aimed to explore event-related signals related to sustainability at the 2022 European Championships in Munich. Drawing upon spectator perspectives and participant observations, we examined how event organizers promoted sustainability at the event, including the contextual and organizational considerations that influenced the interpretations of event sustainability goals. Grounded in signaling theory, the findings revealed that there was a difference in interpretations between bottom-up signals (directly observable) and top-down signals (beliefs and expectations) with respect to the broad understanding of sustainability. These differences were most apparent for spectators concerning social and economic event signals. The directly observable signals emphasized environment-related sustainability, while the top-down signals about social considerations were often overlooked. Event organizers capitalized on some ceremonial moments at the event to bring about greater awareness, but these practices were limited. Event organizers need to consider how to capitalize on both top-down and bottom-up signals to emphasize the sustainability messaging for all stakeholders.

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)0.003
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 score0.821
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0030.000

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 head0.341
Teacher spread0.315 · 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