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Record W3094323334 · doi:10.1123/iscj.2019-0079

Motives for and Experiences of Expatriation to Coach

2020· article· en· W3094323334 on OpenAlexaff
Evelyne Felber Charbonneau, Martin Camiré, Pierre‐Nicolas Lemyre

Bibliographic record

VenueInternational Sport Coaching Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNorwegianCoachingPassionPopularityAthletesPsychologyApplied psychologySocial psychology

Abstract

fetched live from OpenAlex

Coaching is a global profession and coaches play a central role in enhancing the performance of millions of athletes worldwide. In the 21st century, the global mobility of coaches has increased, with many coaches taking advantage of opportunities to coach abroad. Norway leads the all-time Winter Olympics medals table (i.e., 368 medals), and with most of these medals coming from skiing disciplines, Norway represents a skiing hotbed that attracts ski coaches from other parts of the world. The purpose of the study was to examine ski coaches’ motives for and experiences of expatriation to coach in Norway. Five North American alpine ski coaches (four males and one female) were individually interviewed ( M = 77 min, SD = 24.94), with the data examined using interpretative phenomenological analysis. Motives for expatriation included having a passion for skiing, challenging oneself, experiencing a new sport culture, and maintaining relationships. Upon arriving in Norway, coaches mentioned experiencing challenges with the Norwegian sport system, language, pressure from parents and the media, and being far from friends and family. Once acclimated, coaches discussed the benefits of expatriation that included the Norwegian work ethic, family-centric lifestyle, and popularity of skiing.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.039
GPT teacher head0.362
Teacher spread0.324 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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