Perfectionism and performance in sport: Exploring non-linear relationships with track and field athletes
Bibliographic record
Abstract
The relationship between perfectionism – perfectionistic strivings and perfectionistic concerns – and athletic performance is contested and inconsistent. The present study explored the possibility that one explanation for this inconsistency is the assumption that the relationship is linear. In two samples, we tested alternative non-linear relationships between perfectionism and real-world competitive athletic performance. Sample one comprised 165 Swedish track and field athletes (57 % competing in female category, 42 % in male category; Mage = 16.93 years) and sample two comprised 157 British track and field athletes (55 % competing in female category, 43 % in male category; Mage = 18.42 years). Testing for linear and non-linear relationships, we found a quadratic effect whereby higher perfectionistic strivings had both positive increasing (i.e., U-shape; sample 1) and positive decreasing (i.e., inverted U-shape; sample 2) relationships with performance. We conclude that there may be circumstances when perfectionistic strivings contribute to better and worse sport performance, and that this relationship can be curvilinear.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".