A Cluster Analysis of Affective States Before and During Competition
Bibliographic record
Abstract
The purposes of the current study were to identify affective profiles of athletes both before and during the competition and to examine differences between these profiles on coping and attainment of sport goals among a sample of 306 athletes. The results of hierarchical (Ward's method) and nonhierarchical (k means) cluster analyses revealed four different clusters both before and during the competition. The four clusters were very similar at the two measurement occasions: high positive affect facilitators (n = 88 and 81), facilitators (n = 75 and 25), low affect debilitators (n = 83 and 127), and high negative affect debilitators (n = 60 and 73). Results of MANOVAs revealed that coping and attainment of sport achievement goal significantly differed across the affective profiles. Results are discussed in terms of current research on positive and negative affective states.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".