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Record W2113288183 · doi:10.1111/jasp.12083

Situational motivational profiles and performance with elite performers

2013· article· en· W2113288183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Social Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSituational ethicsPsychologyEliteSample (material)AthletesCluster (spacecraft)Social psychologyElite athletesCompetition (biology)Applied psychologyComputer sciencePolitical sciencePhysical therapyChemistry

Abstract

fetched live from OpenAlex

Abstract In S tudy 1, a sample of tennis players ranked at the national level ( n = 173) completed a F rench version of the S ituational M otivation S cale the day before a tennis competition. Results revealed the presence of a three‐cluster solution. Differences among clusters on subsequent sport performance were significant. Specifically, athletes with the least self‐determined motivational profile obtained the lowest levels of performance. S tudy 2 ( n = 319) replicated the findings of S tudy 1 with a larger sample of national level tennis players. Overall, these results suggest that it is useful to analyze individuals' situational motivational profiles using a cluster analysis to understand the complex link between motivation and performance.

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.

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 score0.457
Threshold uncertainty score0.996

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)0.0050.000

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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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