MétaCan
Menu
Back to cohort
Record W2277681376

Debunking disability: media discourse and the Paralympic Games

2012· book-chapter· en· W2277681376 on OpenAlexaboutno aff
Maxine Newlands

Bibliographic record

VenueResearchOnline at James Cook University (James Cook University) · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesHEROEliteGlobeMedia studiesElite athletesGender studiesPolitical sciencePsychologySociologyMedicineArtPhysical therapyLiteratureLaw
DOInot available

Abstract

fetched live from OpenAlex

[Extract] Newwspaper headlines about Paralympic athletes have previously depicted the Paralympic Games with an emphasis on disability over athleticism. Headlines such as 'Public is often blind to some athletes' (The Globe and Mail, Canada, 1993); 'Ready, Willing and Disabled' (Washington Post, 1995); or 'Landmines claim limbs but athletes stand united' (Sydney Morning Herald, Australia, 2000) are just a sample of previous story headlines about Paralympic athletes. The problem many scholars have found is with how language is used by journalists to represent Paralympians is often couched in either medical terms or a 'disabled-hero' (Hardin & Hardin, 2008) discourse with a focus on disability over elite athleticism. Much of the literature has found journalist framed Paralympian stories as negative, passive, medicalised, disability orientated, individualised or focuses on the Paralympics as minority sports, despite being organised in tandem with the Olympic mega-event.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0080.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.044
GPT teacher head0.290
Teacher spread0.246 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueResearchOnline at James Cook University (James Cook University)Same topicSport and Mega-Event ImpactsFrench-language works237,207