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The Cocreation of Place Meaning at Small-Scale Elite Youth-Based Sport Event

2022· article· en· W4226101109 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 Alberta
Fundersnot available
KeywordsMeaning (existential)PsychologyEvent (particle physics)TourismPleasureSpace (punctuation)Relevance (law)Interpretation (philosophy)Social psychologyAdvertisingComputer science

Abstract

fetched live from OpenAlex

The study uses Morgan's model of experience space as a framework for understanding the cocreation of place meaning at the 2017 Canadian Championships in Rhythmic Gymnastics (2017 CCRG). The efforts of event organizers (experience managers and marketers) to shape place experiences at the event was considered in conjunction with the visitors' motivations and their interpretation of meanings inclusive of the social and cultural interactions at the event. Research methods included semistructured interviews and e-mail questionnaires. Five place-based themes emerged through categorical aggregation analysis: function, tourist activities, community, performance, and emotion. These findings demonstrated the relevance of the Morgan's model of experience space. However, modifications to the model were recommended. These include the combination of the achievement, hedonic pleasure and personal meanings components under the label of emotion, and the introduction of a new "performance" component. The 2017CCRG shaped place meaning for athletes, parents, and organizers.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.957

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 science0.0000.000
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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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