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Record W3149308688 · doi:10.1080/19406940.2021.1898442

Legacy and sustainability in the Olympic Movement’s <i>new norm</i> era: when reforms are not enough

2021· article· en· W3149308688 on OpenAlexaff
Robert VanWynsberghe, Inge Derom, Caitlin Pentifallo Gadd

Bibliographic record

VenueInternational Journal of Sport Policy and Politics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegitimationFraming (construction)AccountabilitySustainabilityPolitical sciencePublic administrationPublic relationsCorporate governanceSociologyTerminologyContext (archaeology)LawPoliticsManagementEconomics

Abstract

fetched live from OpenAlex

In times when cities around the world are withdrawing from consideration to host the Olympic Games, the International Olympic Committee (IOC) has responded by enacting policy reforms. Entitled Olympic Agenda 2020: 20 + 20 Recommendations, we examine forty recommendations through the lens of critical policy analysis. Specifically, we use Strittmatter et al.’s framework of legitimation strategies in policy formulation and implementation to investigate the ways in which the use of sustainability and legacy terminology is employed in the process of legitimating the IOC today. Findings demonstrate two general legitimation strategies. One is the familiar framing of the Olympic Games in terms of sustainability and legacy with a new emphasis on the Games as an opportunity to integrate cities’ long-term planning needs into bidding and hosting the event. The second focus asserts the Olympic Movement’s global leadership role in sport in the context of sport itself being depicted as a leading social institution in making meaningful social change. In this paper, we detail these legitimation strategies and offer commentary related to the need for the IOC to use this policy reform process to move beyond rhetoric alone to embed meaningful and measurable accountability standards in the hosting process.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.995

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 communication0.0000.001
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 head0.025
GPT teacher head0.341
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations24
Published2021
Admission routes1
Has abstractyes

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