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Record W2088930714 · doi:10.1037/a0014134

Trajectories of affective states in adolescent hockey players: Turning point and motivational antecedents.

2009· article· en· W2088930714 on OpenAlexafffund
Patrick Gaudreau, Catherine E. Amiot, Robert J. Vallerand

Bibliographic record

VenueDevelopmental Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité du Québec à MontréalUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et CultureUniversité du Québec à Montréal
KeywordsPsychologyAffect (linguistics)Developmental psychologyLongitudinal studyEliteAthletesLatent growth modelingSocial psychologyStatistics

Abstract

fetched live from OpenAlex

This study examined longitudinal trajectories of positive and negative affective states with a sample of 265 adolescent elite hockey players followed across 3 measurement points during the 1st 11 weeks of a season. Latent class growth modeling, incorporating a time-varying covariate and a series of predictors assessed at the onset of the season, was used to chart out distinct longitudinal trajectories of affective states. Results provided evidence for 3 trajectories of positive affect and 3 trajectories of negative affect. Two of these trajectories were deflected by team selection, a seasonal turning point occurring after the 1st measurement point. Furthermore, the trajectories of positive and negative affective states were predicted by theoretically driven predictors assessed at the start of the season (i.e., self-determination, need satisfaction, athletic identity, and school identity). These results contribute to a better understanding of the motivational, social, and identity-related processes associated with the distinct affective trajectories of athletes participating in elite sport during adolescence.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

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 head0.026
GPT teacher head0.321
Teacher spread0.295 · 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.

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

Citations34
Published2009
Admission routes2
Has abstractyes

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