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Record W2990654618 · doi:10.22215/etd/2015-11176

Exercise and Sports Participation: Understanding Student Motivations

2015· dissertation· en· W2990654618 on OpenAlexaff
Adam Lewis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsCarleton University
Fundersnot available
KeywordsExpectancy theoryCompetence (human resources)PsychologyContext (archaeology)Social psychologyPhysical activityIncentiveSample (material)Value (mathematics)Applied psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

The purpose of the present study was to examine motivations for participating in physical activity in an emerging adulthood sample, using Eccles et al.'s (1983) expectancy-value model.Of particular interest was how this model varied for individuals engaging in sports versus exercise.Three hundred and twenty eight undergraduate students completed questionnaires assessing expectancy beliefs, subjective task values, participation indicators as well as health outcomes.Model effectiveness varied as a function of both the activity itself as well as the specific participation indicator.For both sports and exercise activities, however, emerging adults appeared to be more driven by internal rewards (e.g., demonstrating competence, having fun) than by external incentives (e.g., attention and career goals).Findings of the present study partially support the use of the expectancy-value model in this research context, although future research might consider some revision to the measure, to better reflect motivations specific to physical activity engagement.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.088
GPT teacher head0.391
Teacher spread0.303 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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