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Record W4386432014 · doi:10.1123/iscj.2022-0083

“There’s Not a Lot of Glory in What I Do”: Coaches’ Views on Canadian Ice Hockey and Figure Skating Development Programs for Adults

2023· article· en· W4386432014 on OpenAlexaffabout
Courtney Szto, Mary Louise Adams

Bibliographic record

VenueInternational Sport Coaching Journal · 2023
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsQueen's University
Fundersnot available
KeywordsIce hockeyPsychologyWork (physics)Applied psychologyPositive Youth DevelopmentGloryFace (sociological concept)AdvertisingMedical educationEngineeringSociologyDevelopmental psychologyBusinessPhysical medicine and rehabilitationMedicineSocial science

Abstract

fetched live from OpenAlex

Hockey and figure skating are iconic Canadian sports, although it would be hard to know this from the dearth of opportunities available for adults to take up these sports or improve their skills. To learn about the factors that shape adult programming in these two sports, semistructured interviews were conducted with 16 experienced Canadian hockey and figure skating coaches who work with adults. The interviews provided insight into some of the structural barriers that adult learners and their coaches face in hockey and figure skating. Participants suggest that while adult learners are an untapped market, a sport system that privileges high-performance and youth development means that few coaches can make working with adults a priority. Coaches receive little training to work with adults, and because adults are at the bottom of the hierarchy in terms of ice allocation, it is often difficult to design programs that meet their needs. The authors call for more explicit attention to adult programming in hockey and figure skating to meet demand and improve experiences for adults.

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 score0.364
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.348
Teacher spread0.289 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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