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Record W1977483332 · doi:10.1080/16184740903460488

The Assessment of the Environmental Performance of an International Multi-Sport Event

2010· article· en· W1977483332 on OpenAlexaff
Cheryl Mallen, Julie Stevens, Lorne J. Adams, Scott McRoberts

Bibliographic record

VenueEuropean Sport Management Quarterly · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsCanadian Sleep SocietyBrock University
Fundersnot available
KeywordsEvent (particle physics)SustainabilityEvent managementBusinessMarketingPublic relationsProcess managementPsychologyEnvironmental resource managementPolitical scienceCritical success factorEconomics

Abstract

fetched live from OpenAlex

Despite recent calls to reduce the environmental impact of major sporting events, comprehensive measurements, evaluations, and reports on environmental sustainability (ES) within the sport sector are rare. Consequently, the purpose of this multi-method case study was to assess the environmental performance (EP) of an international multi-sport event. Survey and interview data were collected from 15 event managers and executive volunteers (N=15). The findings indicated the event organization demonstrated a high level of effort towards initiating an ES movement within the Games but ultimately achieved a weak to moderate level of EP. Further, structural, systemic and cultural organization barriers prevented the implementation of many ES policies and programs. Sport event EP success is contingent upon organizers understanding both the operational reality in which they must stage the event, and their strategic capability to fulfill this goal.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.286
Teacher spread0.276 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations97
Published2010
Admission routes1
Has abstractyes

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