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Record W1968286637 · doi:10.1177/1012690209104798

Public Broadcasting, Sport, and Cultural Citizenship

2009· article· en· W1968286637 on OpenAlexaffabout
Jay Scherer, David Whitson

Bibliographic record

VenueInternational Review for the Sociology of Sport · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsContext (archaeology)CitizenshipPublic broadcastingCompetition (biology)Political scienceLeagueBroadcasting (networking)AdvertisingPublic relationsSociologyMedia studiesLawPoliticsBusinessHistory

Abstract

fetched live from OpenAlex

In this article we examine the recent debate over the continued role of the Canadian Broadcasting Corporation (CBC) in airing National Hockey League (NHL) games on its iconic television show, Hockey Night in Canada (HNIC) . Specifically, we outline the heightened competition between the CBC and private networks for the most desirable sports rights in the context of the explosive growth of subscription television. We then review how the CBC was, in the face of this competition and to the surprise of many commentators, able to secure a new contract with the NHL in 2006. We argue here that, while Canada's public network will never again have the place in Canadian life that it had in the early days of television (Rutherford, 1990), HNIC remains an important investment because it acts as a critical promotional platform for the public network, as well as providing a sizeable revenue stream that subsidizes the network's other programming. We will also argue that providing free-to-air broadcasts of the sport that matters most to Canadians is an issue of cultural citizenship, and thus an important part of the mandate of a public broadcaster, and a matter of national interest.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.350
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.015
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.119
GPT teacher head0.397
Teacher spread0.278 · 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

Citations34
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueInternational Review for the Sociology of SportSame topicSport and Mega-Event ImpactsFrench-language works237,207