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Record W2598979802 · doi:10.1123/tsp.2018-0037

Achievement Despite Adversity: A Qualitative Investigation of Undrafted National Hockey League Players

2019· article· en· W2598979802 on OpenAlexaff
Jordan D. Herbison, Luc J. Martin, Mustafa Sarkar

Bibliographic record

VenueThe Sport Psychologist · 2019
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsQueen's University
Fundersnot available
KeywordsAmateurLeaguePsychologyAthletesEliteIce hockeyContext (archaeology)Elite athletesPerceptionApplied psychologySocial psychologyPhysical therapyPolitical scienceMedicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Adversity is viewed as both an inevitable and an important experience for elite athletes. The purpose of this study was to explore elite athletes’ perceptions of the experiences and characteristics that helped them overcome a shared sport-specific adversity. Semistructured interviews were conducted with 12 professional athletes ( M age = 27.25, SD = 3.28 yr) who had progressed to careers in the National Hockey League (NHL) despite not being selected in the annual amateur entry draft. Participants discussed their long-term objectives of playing in the NHL, previous experiences with adversity, certain psychological characteristics that facilitated their progression (e.g., competitiveness, passion, confidence), and the significance of social support as key factors that helped them overcome the initial and subsequent adversities associated with being unselected during the amateur entry draft. Practical implications and proposed avenues for future research are discussed in the context of the study’s limitations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.057
GPT teacher head0.377
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; both teacher heads agree on what is shown here.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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