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Record W2888895327 · doi:10.21511/ppm.16(3).2018.26

The business effects of mega-sporting events on host cities: an empirical view

2018· article· en· W2888895327 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

VenueProblems and Perspectives in Management · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsYorkville UniversityUniversity of British Columbia
Fundersnot available
KeywordsPromotion (chess)Sample (material)Event (particle physics)Host (biology)MarketingEmpirical researchBusinessEmpirical evidenceAdvertisingPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The study is an empirical view of the important issue of the business effects of the mega-sporting events (MSEs), like the Olympic Games, on which there are favorable and unfavorable views, the design of the study is to go through different views and find out the effects from knowing or knowledgeable persons of the event with the help of a sample of 155 respondents drawn randomly from across the continents in the form of opinions on the positive and negative effects of the MSEs through a questionnaire, containing questions on economic development, infrastructure development, environ¬ment, lifestyles, etc., and their favorable and unfavorable responses were elicited. The data collected have been analyzed in terms of the characteristics of respondents and their negative and positive responses on the Olympic and FIFA. The findings on the whole of study show that the hosting of the MSEs has positive effects on the economy and society of the host cities through the influx of tourists, infrastructure development, and image promotion of the country, among others, notwithstanding the certain drawbacks in terms of environmental disturbances, and some inconveniences to the locals.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.330

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 studies0.0000.000
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 head0.056
GPT teacher head0.358
Teacher spread0.302 · 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