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Record W216971157

Tendències o direccions de l'esport contemporani en funció dels motius de la pràctica : un estudi empíric entre els estudiants de la Universitat d'Oviedo

2003· article· ca· W216971157 on OpenAlexaboutno aff
José Antonio Cecchini Estrada, A. Giménez, José Muñiz Fernández

Bibliographic record

VenueApunts. Educació física i esports · 2003
Typearticle
Languageca
FieldSocial Sciences
TopicSports and Physical Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Les investigacions descriptives sobre els motius que porten els joves a practicar l’esport, desenvolupades majoritariament als Estats Units i a paisos anglofons, com ara Gran Bretanya, Australia i el Canada, han mostrat de forma consistent una estructura multifactorial. La majoria s’emmarquen dintre de la perspectiva cognitivosocial i es recolzen en el concepte de motivacio d’assoliment. A partir d’aquests resultats, el nostre objectiu ha estat analitzar l’estructura ‘motivacional’ subjacent, amb l’objecte de determinar les tendencies mes acusades de l’esport contemporani. Els joves sotmesos a enquesta, 2.689, son estudiants de la Universitat d’Oviedo (1.440 homes i 1.249 dones). Tots ells van respondre questionari dissenyat amb aquesta finalitat. Els resultats evidencien una doble estructura bipolar que sembla respondre a la ‘binaritzacio’ de dos criteris: competicio (C) i mestratge (M). La seva presencia o absencia origina un arbre dicotomic de quatre branques. Aquests quatre subgrups mostren, a mes a mes, unes peculiaritats derivades de les diferencies de genere, tipus d’activitat i intensitat de la motivacio vers l’esport. Finalment, es discuteixen els resultats i se n’extreuen algunes conclusions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.007
GPT teacher head0.308
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2003
Admission routes1
Has abstractyes

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