Dispositional perfectionism and well-being: A test of the 2 × 2 model of perfectionism in the sport domain.
Bibliographic record
Abstract
In the 2 2 model of dispositional perfectionism, we posit that four within-person combinations of self-oriented (SOP) and socially prescribed (SPP) perfectionism (i.e., high/high, high/low, low/high, low/low) can be distinguished on the basis of their distinct etiological and functional features. The goal of this study was to examine whether subtypes of perfectionism are distinctively associated with subjective wellbeing (i.e., positive affect, subjective vitality, and life-satisfaction) in the sport domain. Showing that pure SOP is associated with either better (Hypothesis 1a), worse (Hypothesis 1b), or equivalent (Hypothesis 1c) psychological outcomes (compared to nonperfectionism) would respectively support the potentially healthy, unhealthy, and neutral nature of SOP. Conversely to prior literature, pure SPP is hypothesized to be the most damaging subtype of perfectionism in the 2 2 model of perfectionism (Hypothesis 2). As such, the tenets of the 2 2 model differ from the literature by suggesting that mixed perfectionism is potentially less harmful compared to a subtype of pure SPP (Hypothesis 3), but potentially more harmful compared to a pure SOP (Hypothesis 4). Results of moderated multiple regression analyses have shown that pure SOP is associated with equally high levels of positive affect and vitality, and to significantly higher levels of life-satisfaction compared to nonperfectionism. Furthermore, pure SPP was associated with significantly lower levels of positive affect, vitality, and life-satisfaction compared to other subtypes of perfectionism. This study provided initial support for most of the hypotheses of the 2 2 model of perfectionism in the sport domain.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".