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Record W4389884787 · doi:10.30958/ajspo.10-4-3

Olympic Public Transportation Investments, Legacy, and City Prosperity: An Empirical Look at the 2000-2016 Summer Games

2023· article· en· W4389884787 on OpenAlex
Kennedy Magee, W. James Weese

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

VenueAthens Journal of Sports · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsProsperityPublic transportIndex (typography)BusinessPublic parkAdvertisingMarketingEconomicsEconomic growthGeographyTransport engineeringEngineeringEnvironmental planningComputer science

Abstract

fetched live from OpenAlex

The complexity of hosting the Olympic Games has grown throughout its history. The financial risks to cities vying for the hosting rights are often viewed as excessive and consequently, fewer bids are being submitted in modern times. Critics suggest that public funds would be better spent supporting other social programs. However, history has demonstrated that host cities can use the Games to expand and modernize public transport systems to efficiently move people, increase accessibility, reduce personal travel and garner environmental benefits like improved air quality and less noise pollution. The authors examined the five Summer Olympic Games host cities between 2000-2016 using the City Prosperity Index (CPI) to measure city performance across six indexes to determine the accrued public transit benefits of hosting the Games. The authors hope this paper can provide a clear path forward for future Olympic bidders and city officials. Keywords: Olympic Games, City Prosperity Index, public transportation, investments

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.629

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.347
Teacher spread0.273 · 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