MétaCan
Menu
Back to cohort
Record W3197854236 · doi:10.1123/jsm.2020-0117

Examining the Efficacy of a Government-Led Sport for Development and Peace Event

2021· article· en· W3197854236 on OpenAlexaff
Gareth J. Jones, Elizabeth Taylor, Christine Wegner, Colin López, Heather Kennedy, Anthony P. Pizzo

Bibliographic record

VenueJournal of Sport Management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEvent (particle physics)Government (linguistics)Public relationsEvent managementPolitical scienceLocal governmentPsychologyBusinessMarketingPublic administrationCritical success factor

Abstract

fetched live from OpenAlex

A large body of research has examined the influence of sport for development and peace (SDP) events on community development, focusing primarily on SDP events delivered by nonprofit “change agents.” Although scholars have highlighted the need to more meaningfully incorporate local governments into SDP event management, there has been limited attention to government-led implementation. The purpose of this study was to explore a government-led SDP event through the lens of the S4D Framework to understand how the approach to implementation influenced sport event management, direct social impacts, and long-term social outcomes. Data were generated primarily through interviews with members of the event leadership team and supplemented with observations and focus groups with event participants. The findings indicate that the structural and social resources of the local government were key to activating different phases of the S4D Framework, yet also revealed unique challenges that have important implications for SDP event management.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.300

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 communication0.0000.000
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 head0.040
GPT teacher head0.306
Teacher spread0.266 · 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 designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sport ManagementSame topicSport and Mega-Event ImpactsFrench-language works237,207