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Explaining Festival Impacts on a Hosting Community Through Motivations to Attend

2016· article· en· W2340333088 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvent Management · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsExtant taxonSociocultural evolutionScale (ratio)Music festivalPsychologyExploratory factor analysisTourismSocial impactAdvertisingSociologyGeographyBusinessDemographyDevelopmental psychologyAnthropology

Abstract

fetched live from OpenAlex

Extant literature on social–cultural impacts of festivals traditionally takes into consideration perspectives of the host community while neglecting those of visitors, who often times comprise a high percent of total number of attendees at such expositions. Additionally, motivations of these visitors to attend festivals have rarely been considered in explaining perceived impacts among festival attendees. This study examined the underlying structures of motivations to attend the annual Morden Corn and Apple Festival, Manitoba, Canada among area residents and visitors as well as their perceived sociocultural impacts of the festival on community through a newly developed festival-attending motivation scale and modified Festival Social Impact Attitude Scale (FSIAS). Exploratory factor analysis and multiple regression results suggested that at least one motivation factor (i.e., social interaction and/or knowledge gain ) significantly predicted three of the four modified FSIAS factors.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.789

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 head0.086
GPT teacher head0.374
Teacher spread0.288 · 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