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Record W4291670791 · doi:10.3390/su14169874

Strategic Sustainable Development in International Sport Organisations: A Delphi Study

2022· article· en· W4291670791 on OpenAlexaff
Iva Glibo, Laura Misener, Joerg Koenigstorfer

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsWestern University
Fundersnot available
KeywordsDelphi methodSustainabilityBusinessStrategic planningDelphiSustainable developmentProcess managementBiddingNormativeStrategic environmental assessmentKnowledge managementStrategic managementMarketingPolitical scienceComputer scienceEnvironmental impact assessment

Abstract

fetched live from OpenAlex

The study aims to explore the consensus-level strategic priorities for sustainable development from the perspective of decision makers in organisations responsible for governing international sport and how they cluster within the Framework for Strategic Sustainable Development. We employed the three-round Delphi study with decision makers from international sport organisations. Based on the 29 semi-structured interviews in the first round, we inductively generated items for questionnaires for the subsequent two rounds. The process yielded 20 items representing strategic priorities determined by 20 experts in the last round. The highest ranked item was normative change, in which sustainability is prioritised throughout all organisational strategies and actions. Moreover, planned efforts that are part of a long-term strategy and embedding sustainability requirements at the bidding phase of sport events were considered with high priority. The 20 items clustered into four out of five levels of the Framework for Strategic Sustainable Development, namely system, success, strategic guidelines and actions. No items could be assigned to the framework’s tool level, potentially indicating gaps of strategic consideration. The findings from the Delphi study add a forecasting element to the research and practice of strategic sustainability in the management of sport by revealing consensus-level strategic priorities for the future.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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 teacher head, not a consensus.

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

Citations17
Published2022
Admission routes1
Has abstractyes

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