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Record W4310470873 · doi:10.1080/2159676x.2022.2152084

Exploring athletes’ and classifiers’ experiences with and understanding of classification in Para sport

2022· article· en· W4310470873 on OpenAlex
Janet A. Lawson, Toni L. Williams, Amy E. Latimer‐Cheung

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

VenueQualitative Research in Sport Exercise and Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAthletesContext (archaeology)PsychologyEmpirical researchStatistical classificationApplied psychologyArtificial intelligenceComputer scienceMedicinePhysical therapyMathematics

Abstract

fetched live from OpenAlex

Classification is a defining feature of Para sport; however, little empirical evidence describes the experience of classification and how it can be improved. To date, the primary focus of research related to classification has been on the development of evidence-based classification procedures. Meanwhile, the limited literature which has focused on experiential aspects of classification has shown classification to be a potentially negative experience for athletes. As well, classifiers have been identified as important social actors within the Para sport context, yet no research has examined both athletes’ and classifiers’ experiences with classification. The experiences of athletes and classifiers have yet to be considered alongside one another. Therefore, the purpose of this study was to elucidate athletes’ and classifiers’ experiences with classification in Para sport. Semi-structured interviews exploring the experience of classification were conducted with 18 internationally classified Canadian athletes and an international sample of eight classifiers. Hermeneutic phenomenological analysis was used to conceptualise athletes’ and classifiers’ classification experience. Results demonstrate athletes and classifiers learn about classification by observing others and reflecting on their own understanding of their body or skillset in relation to classification. Additionally, we show how interactions between athletes and classifiers influence each parties’ experience quality and highlight discrepancies between each groups’ understandings of classification. Next, we provide recommendations for future research to address the identified gaps in athletes’ and classifiers’ understanding of classification. Lastly, through the provision of practical recommendations, this work may support Para sport practitioners in improving athletes’ and classifiers’ experiences with classification.

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)0.013
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.173
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.733
GPT teacher head0.585
Teacher spread0.147 · 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