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Record W2994523041 · doi:10.1080/14927713.2019.1697348

From organized sport motivation to exercise regulations: differences according sport type and intensity

2019· article· en· W2994523041 on OpenAlexvenueaboutno aff
Jean Lemoyne, Marie-Claude Rivard, Stéphanie Girard, Pascal Dubreuil

Bibliographic record

VenueLeisure/Loisir · 2019
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyIntensity (physics)Exercise intensityApplied psychologyPhysical therapyPhysical medicine and rehabilitationMedicinePhysics

Abstract

fetched live from OpenAlex

Motivation to take part in sufficient levels of physical activity (PA) is a common problem during adolescence. This study investigated associations between motive for sport participation and behavioral regulations towards PA practice. A cohort of 1804 adolescents involved in a large organized sport event, ‘Quebec’s Summer Games Final’ completed questionnaires preceding their participation to the games. Fifteen sports were represented and categorized regarding sport type (team versus individual) and intensity (moderate versus high). Group comparisons were conducted with invariance testing. In summary, motives for competition were significantly associated with identified and intrinsic motivation. Motives for fitness-health were significantly associated with identified motivation, and motives for socialization were significantly associated with external motivation. Significant differences were observed, when comparing the level of intensity and sport type. Such differences are attributed to sport culture and from the participants’ selection process. This study suggests stakeholders to consider approaches that will develop self-determined regulations among those who are involved in particularly moderate intensity activities.

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 score0.005
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.277
Teacher spread0.249 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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