MétaCan
Menu
Back to cohort

"Not on My Front Lawn": A Case Study of Hosting the 2017 Heritage Classic Event on Parliament Hill in Canada

2021· article· en· W3204300138 on OpenAlexaffabout
Cory Kulczycki, Jonathon Edwards, Luke R. Potwarka

Bibliographic record

VenueEvent Management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of WaterlooUniversity of New BrunswickUniversity of Regina
Fundersnot available
KeywordsParliamentNarrativeMedia studiesCultural heritageEvent (particle physics)SociologyInstitutionFront (military)Consolidation (business)Political scienceHistoryLawSocial scienceArtPoliticsGeographyLiterature

Abstract

fetched live from OpenAlex

The purpose of this research was to explore different issues and controversies found in media narratives about hosting the Heritage Classic Ice-Hockey Game on Canada's Parliament Hill. This article utilized the eight-step qualitative-temporal visual analysis and narrative methodology to look at how Canadian media framed the discussion around the hosting location of the Heritage Classic. A total of 81 news articles from 12 media outlets served as the data for the current study. Media frames were grouped into seven themes: parliamentary rules, interest groups, anniversaries, logistics, competition, event landscape, and nostalgia. These frames point to how Parliament Hill was maintained as an institution through regulations and symbolism. The following manuscript informs research on institutional work through applications of special events, eventscapes, and nostalgia.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0340.012
Scholarly communication0.0080.002
Open science0.0030.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.045
GPT teacher head0.312
Teacher spread0.268 · 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 designQualitative
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

Citations1
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueEvent ManagementSame topicSport and Mega-Event ImpactsFrench-language works237,207