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Record W2936604379 · doi:10.1123/cssep.2019-0002

Catch the Feeling of Flying: Guided Walks Through a Trampoline Olympic Development Environment

2019· article· en· W2936604379 on OpenAlexaffabout
Michelle Seanor, Robert J. Schinke, Natalia Stambulova, Kristoffer Henriksen, Dave Ross, Cole E. Giffin

Bibliographic record

VenueCase Studies in Sport and Exercise Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsLaurentian University
Fundersnot available
KeywordsChampionContext (archaeology)MedalNarrativeFeelingTrampolinePresentation (obstetrics)Theme (computing)PortraitPsychologyEngineeringVisual artsPolitical scienceSocial psychologyGeographyArtComputer science

Abstract

fetched live from OpenAlex

Olympic-medal performances represent peak accomplishments in athlete development. Seanor, Schinke, Stambulova, Ross, and Kpazai identified environmental factors in a high-performance Canadian trampoline sport environment that developed decorated Olympic medalists. The current intrinsic case study was authored to further highlight the idiosyncrasies of a high-performance trampoline environment (re)presenting stories garnered from this localized Canadian sport environment. Through guided walks, a mobile method of conversational interviews, three contextual experts who are engaged in the development of Olympic athletes provided tours of their sport environment. Each contextual expert’s guided walk played out uniquely in relation to his or her ascribed role (i.e., Olympic coach, assistant coach, and Olympic champion). Three main themes were identified through interpretive thematic analysis: creating lift (subthemes: facility design, sport-culture paragons), providing a tailwind (subthemes: establishing athlete–coach partnerships, team interactions), and soaring onto the Olympic podium (subthemes: preparing athletes to be untethered, competitive collaboration). Each theme is presented through three portrait vignettes, with discrete vantages derived from each contextual expert to illuminate the context from idiosyncratic ascribed roles within the environment. These stories create a rich (re)presentation of a high-performance sport environment through the interplay of the contextual experts’ narratives, their surrounding context, and their Olympic-podium accomplishments.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.074
GPT teacher head0.386
Teacher spread0.312 · 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

Citations9
Published2019
Admission routes2
Has abstractyes

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