MétaCan
Menu
Back to cohort
Record W2164794596 · doi:10.1504/ijsmm.2007.013714

Sport and civic engagement: community governance and the sport policy process

2007· article· en· W2164794596 on OpenAlexafffundabout
Michelle Rose

Bibliographic record

VenueInternational Journal of Sport Management and Marketing · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Ottawa
FundersFederation of Canadian Municipalities
KeywordsJurisdictionPublic administrationCorporate governanceRecreationPoliticsInterdependenceGovernment (linguistics)State (computer science)Political sciencePublic relationsBusinessLawFinance

Abstract

fetched live from OpenAlex

As the primary providers of sporting amenities, municipal governments have a substantial responsibility for the delivery and administration of sport in Canada. However, the responsibilities for sport and recreation have traditionally been a provincial jurisdiction. Within the last decade, sport policies in Canada have emerged from all levels of government. Due to the dynamic and often complex nature of Canada's federal system of government, relationships between federal, provincial and municipal levels have evolved to deal with the interdependencies and overlap of political jurisdictions. It is the purpose of this study to examine how changing policy priorities and territoriality over the jurisdiction of sport have forced municipal governments to seek alternative sources of political and financial leadership and how municipalities have evolved to deal with the complexities of Canadian federalism to become legitimate players in the sport policy process. More specifically, this paper examines how community governance has emerged from the contestation period of the welfare state to explain current trends in state intervention in sport.

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)0.013
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.000
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 head0.018
GPT teacher head0.326
Teacher spread0.308 · 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 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

Citations7
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Sport Management and MarketingSame topicSport and Mega-Event ImpactsFrench-language works237,207