Persistence in a Putting Task During Perceived Failure: Influence of State‐attributions and Attributional Style
Bibliographic record
Abstract
Dans cette étude, on a examiné l’influence de l’état des attributions et le style attributionnel (AS) sur la persistance à court‐terme d’un échec perçu à une tâche de putting. 101 élèves débutants en golf ont participéà cette recherche. Deux épreuves de 8 putts ont été interrompues chacune pendant trois minutes. Durant cette période, on a mesuré la persistance individuelle en comptant le nombre de fois que le sujet essayait de putter. L’analyse des résultats montre que le style attributionnel influence la persistance à court‐terme contrairement à l’état des attributions. Les sujets ayant un AS “fort contrôle personnel” font montre de plus de persistance que ceux ayant un AS “faible contrôle personnel”. Ces résultats confirment ceux obtenus lors de recherches antérieures sur les bénéfices motivationnels d’un style attributionnel “optimiste” dans des situations d’échec lors de la réalisation d’une tâche. Des attributions instables sont particulièrement bénéfiques aux sujets ayant un AS externe/incontrôlable. Ces derniers ont un niveau significativement plus élevé de persistance que les sujets ayant un AS externe/incontrôlable mais qui ont fait des attributions causales stables. This study investigated the influence of state‐attributions and attributional style (AS) on short‐term persistence in a putting task during perceived failure. Participants were 101 novice golf students. Two trials of eight putts each were interrupted by a 3‐minute free period during which individual persistence was measured by calculating the number of putts attempted in the free period. Analyses revealed that attributional style influenced short‐term putting persistence but state‐attributions did not. Participants with a “high personal control” AS showed greater persistence than those with a “low personal control” AS, which supports past research on the positive motivational benefits of a more “optimistic” attributional style in task failure situations. Moreover, unstable attributions were particularly protective for individuals with an external/uncontrollable AS, in that they promoted significantly higher levels of persistence than was shown by external/uncontrollable AS individuals who made stable causal attributions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".