MétaCan
Menu
Back to cohort
Record W2988837308 · doi:10.1016/j.smr.2019.10.002

Design archetype utility for understanding and analyzing the governance of contemporary national sport organizations

2019· article· en· W2988837308 on OpenAlexaff
Russell Hoye, Milena M. Parent, Marijke Taks, Michael L. Naraine, Benoît Séguin, Ashley Thompson

Bibliographic record

VenueSport Management Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsBrock UniversityUniversity of Ottawa
Fundersnot available
KeywordsArchetypeCorporate governanceOrganizational changeSociologyRepresentation (politics)Perspective (graphical)Knowledge managementPublic relationsPolitical scienceManagementComputer science

Abstract

fetched live from OpenAlex

Highlights• Design archetypes are central to exploring change dynamics in NSOs.• NSOs must strategically adapt and change to be effective.• New ways to improve the representation of design archetypes for contemporary NSOs.• Future research agenda to help understand change within NSOs.

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)0.026
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0110.010
Science and technology studies0.0020.013
Scholarly communication0.0100.013
Open science0.0030.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.130
GPT teacher head0.350
Teacher spread0.220 · 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 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

Citations37
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSport Management ReviewSame topicSport and Mega-Event ImpactsFrench-language works237,207