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Record W3148784614 · doi:10.1123/ijatt.2019-0117

Athletic Trainers’ Experiences Working With Athletes With a Physical Disability in School-Based Sports

2021· article· en· W3148784614 on OpenAlexaboutno aff
Alison R. Snyder Valier, Kelsey J. Picha, Deanne Fay

Bibliographic record

VenueInternational Journal of Athletic Therapy & Training · 2021
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesPsychologyPhysical therapyQuarter (Canadian coin)Medical educationAthletic trainingMedicine

Abstract

fetched live from OpenAlex

This study describes the experiences of over 500 school-based athletic trainers (ATs) and their familiarity, knowledge, comfort, and confidence working with athletes with a disability. ATs’ experiences in managing the health care of school-based athletes with a physical disability are unknown. Half of the respondents indicated experience providing services to these athletes, while 70% indicated little to no specific training/education. About half of the ATs reported being comfortable and confident in managing the care of athletes with a physical disability, while a quarter reported being knowledgeable. Findings suggest that experience helps provide ATs with comfort and confidence in caring for these athletes, but educational opportunities are still needed.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.079
GPT teacher head0.399
Teacher spread0.320 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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