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Record W2149223855 · doi:10.1123/ssj.21.1.36

From Corporate Welfare to National Interest: Newspaper Analysis of the Public Subsidization of NHL Hockey Debate in Canada

2004· article· en· W2149223855 on OpenAlexfundaboutno aff
Jay Scherer, Steven J. Jackson

Bibliographic record

VenueSociology of Sport Journal · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsSubsidyNewspaperGovernment (linguistics)LeaguePolitical sciencePoliticsPublic administrationNational identityWelfareIce hockeyPolitical economySociologyLaw

Abstract

fetched live from OpenAlex

Despite the historic and popular alignment of ice hockey with Canadian identity, the public subsidization of National Hockey League (NHL) franchises remains a highly contentious public issue in Canada. In January 2000 the Canadian government announced a proposal to subsidize Canadian-based NHL franchises. The proposal, however, received such a hostile national response that only three days after its release an embarrassed Liberal government was forced to rescind it. This article explores how Canadian anglophone newspapers mediated the NHL subsidy debate and emerged as critical sites through which several interrelated issues were contested: the subsidization of NHL franchises, competing discourses of Canadian national identity, and the broader political-economic and sociocultural impacts of the Canadian government’s adherence to a neoliberal agenda.

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)0.012
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 score0.131
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.012
Science and technology studies0.0240.013
Scholarly communication0.0150.002
Open science0.0010.003
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 head0.050
GPT teacher head0.286
Teacher spread0.236 · 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

Citations25
Published2004
Admission routes2
Has abstractyes

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