The dynamic nature of daily affect and its relation to role perceptions in youth sport
Bibliographic record
Abstract
Given the salience of emotions in sport and their connectedness to the dynamic environment surrounding athletes, this study explored how daily variation in affect was related to role perceptions in interdependent sport teams. We examined (a) the daily within-person variance of positive and negative affect and (b) how variations in role satisfaction and clarity related to daily fluctuations in positive and negative affect. Using ecological momentary assessment, 110 youth ice hockey players (aged 14-17 years) completed daily self-report questionnaires through a smartphone application. Athletes provided an average of 8.15 responses (N = 896 observations) pertaining to positive affect (excited, proud, determined), negative affect (irritable, upset, distressed), and perceptions of role satisfaction and clarity within their teams. Data were analyzed using multilevel structural equation modeling. Intraclass correlation coefficients showed substantial variance in daily affect at both within- (45.9 %-62.7 %) and between-person (37.3 %-49.7 %) levels. The within-person associations showed that role perceptions and affect fluctuated together across time-points. Athletes reported higher positive affect (β = 0.25, p < .001, 95 % CI [0.14, 0.36]) and lower negative affect (β = -0.28, p < .001, 95 % CI [-0.42, -0.14]) on days when they had higher-than-average levels of role satisfaction. They also reported higher positive affect (β = 0.23, p < .001, 95 % CI [0.11, 0.41]) and lower negative affect (β = -0.30, p < .001, 95 % CI [-0.45, -0.15]) on days when they reported higher-than-average levels of role clarity. These findings reinforce the variability of affective experiences and emphasize the important associations with group-related phenomena such as role perceptions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".