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Record W3212488904 · doi:10.1123/apaq.2021-0095

Pathways in Paralympic Sport: An In-Depth Analysis of Athletes’ Developmental Trajectories and Training Histories

2021· article· en· W3212488904 on OpenAlexaffabout
Nima Dehghansai, Ross A. Pinder, Joseph Baker

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2021
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsYork University
Fundersnot available
KeywordsAthletesPacePsychologyPhysical therapyDevelopmental psychologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

This three-part investigation conducted a comprehensive analysis of 213 Australian and Canadian athletes' developmental trajectories, training histories, and experiences in organized sports from 18 Paralympic sports (PS). While athletes with early-onset impairments (i.e., congenital, preadolescent) reached milestones and commenced various types of training at a significantly younger age than athletes with later-onset impairments (i.e., early adulthood, adulthood), the latter groups progressed through their careers and incorporated various trainings at a faster pace (i.e., fewer years). Preferences to certain training conditions varied between groups. Eighty-two percent of the athletes with acquired impairments had experience in able-bodied sports before the onset of their impairment, with 70% noting involvement in sports similar to their current PS. The participation rates (38%) and sport similarity (53%) were lower in PS. The amalgamation of findings from this series of studies highlights the complexity associated with PS athletes' development and demonstrates the importance of taking an individualized approach.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.065
GPT teacher head0.332
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2021
Admission routes2
Has abstractyes

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