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Record W3016819033 · doi:10.15203/ciss_2020.002

Developmental pathways of Para athletes: Examining the sporting backgrounds of elite Canadian wheelchair basketball players

2020· article· en· W3016819033 on OpenAlex
Srdjan Lemez, Nick Wattie, Nima Dehghansai, Joseph Baker

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCurrent Issues in Sport Science (CISS) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsYork UniversityOntario Tech University
Fundersnot available
KeywordsBasketballAthletesElitePsychologyWheelchairCohortTeam sportNorwegianPhysical therapyApplied psychologyMedicinePolitical scienceGeography

Abstract

fetched live from OpenAlex

This study examines developmental history data to identify common pathways for elite Para sport performance and contextualizes these findings using known models of athlete development (e.g., the Developmental Model of Sport Participation, Côté, 1999). Seventy-three Canadian wheelchair basketball players completed a modified version of the Developmental History of Athletes Questionnaire (Hopwood, 2013). Overall, the results emphasized considerable variability in measures related to ‘other’ organized sport participation regardless of disability status and competition level, including the proportion of participants that participated in at least one other sport, the number of other sports participated in, the age first participated in other sports, and the number of years spent participating in other sports. This variability suggests there may be multiple Para athlete development narratives and highlights a need for more evidence-based models that are sufficiently nuanced for this athlete cohort.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.115
GPT teacher head0.372
Teacher spread0.257 · 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