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Record W4413955317 · doi:10.1080/16138171.2025.2555649

‘Third era’ parasport athletes and athlete ‘volunteer’ appearances (AVAs): a relational analysis

2025· article· en· W4413955317 on OpenAlexaff
Luke Jones, Haydn Morgan, Anthony Bush, Alison Smith, Darryn Stamp, P. David Howe

Bibliographic record

VenueEuropean Journal for Sport and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsWestern University
FundersNational Lottery Community Fund
KeywordsAthletesVolunteerPsychologyAdvertisingSociologyBusinessPhysical therapyMedicine

Abstract

fetched live from OpenAlex

In the ‘third era’ of Paralympic sport (Howe, Citation2008), there has been a discernable shift in focus towards high performance outcomes, fuelled by dramatic increases in funding and medal expectations. With these increases there have been significant implications for the lived experiences of Parasport eligible disabled athletes. This shift has facilitated more freedom and allayed some of the concerns/energies required to facilitate dual-career activities and in turn, allowed for greater commitment to their Parasport careers. However, as this paper will explore, there are other aspects of Paralympic athletes’ lives influenced by this development that remain under explored – including the fact that classifiably eligible disabled athletes are required, as are their able bodied peers, to contribute to schemes where their role as a visible asset is harnessed in the form of athlete ‘volunteer’ appearances (AVAs). In response, this paper draws upon the relational theorising of Crossley (Citation2011) to analyse data from a multiple case study approach in order to consider the implications of an array of athlete ‘volunteer’ appearances (AVAs) performed by nine Paralympic athletes across a range of sports.

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 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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.292
Teacher spread0.268 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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