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Record W2804498563 · doi:10.1177/2167479518775427

Framing the Olympic Elite Athlete Funding Issue: A Case Study of Canadian Newspaper Coverage

2018· article· en· W2804498563 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCommunication & Sport · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFraming (construction)EliteNewspaperPolitical sciencePublic relationsMedia coverageAmbush marketingMedalAthletesSociologyAdvertisingMedia studiesPoliticsHistoryLawBusiness

Abstract

fetched live from OpenAlex

This article employs media framing theory to examine the debate over public funding to support elite athlete development. More specifically, it examines the discourse in Canadian newspaper coverage of the 2010 Vancouver Olympic Games surrounding funding for elite athletes. The article first provides an overview of government funding support for elite athletes in Canada and then reviews relevant literature on media framing theory. Methods are discussed, followed by a summary of the frames found in the data analysis process, which examines frames across two distinct time periods—a period leading up to the Games where many stakeholders worried about the ability of Canadian athletes to perform for the host country and the period during and following the Games (where Canadian athletes achieved unprecedented success in winning medals). Several frames emerged from the media coverage regarding the issue of federal government funds for elite athletes over the periods before and during/after the 2010 Olympic Games. Through examining the frequencies of particular frames, we find that three frames—medal performance and national pride, diversified funding approaches, and sport participation and health benefits—were present in both pre-Olympics and during/post-Olympics periods examined, but the salience of the three frames varied between the time periods.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.069
GPT teacher head0.351
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