MétaCan
Menu
Back to cohort
Record W2607274039 · doi:10.1177/1748048516689194

On thin ice: <i>Hockey Night in Canada</i> and the future of national public service media

2017· article· en· W2607274039 on OpenAlexaboutno aff
Christopher Cwynar

Bibliographic record

VenueInternational Communication Gazette · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsIce hockeyPublic servicePublic broadcastingService (business)CriticismPublic relationsMass mediaSociologyPolitical scienceMedia studiesAdvertisingBusinessMarketingLaw

Abstract

fetched live from OpenAlex

This article considers the implications of rising sports rights fees and emerging digital media technologies for legacy public service broadcasters. I argue that, while the Hockey Night in Canada sublicensing agreement with Rogers prompted a significant amount of criticism of the CBC at the time, it is consistent with the broader history of the program. Furthermore, the situation is most significant in that it exposes the tensions between the CBC and the marketplace as manifested in CBC-TV. I suggest that this deal illustrates that the CBC should exit the commercial television marketplace. I conclude by suggesting that the CBC should shift its focus toward a renewed emphasis on noncommercial programming in areas often neglected by the commercial media. This approach could potentially provide a model for how legacy public service media institutions might reassert their civic and cultural value in an increasingly convergent and commercialized mediascape.

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 score0.092
Threshold uncertainty score0.664

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.012
Scholarly communication0.0190.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0170.001

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 head0.033
GPT teacher head0.314
Teacher spread0.282 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Communication GazetteSame topicSport and Mega-Event ImpactsFrench-language works237,207