Daily Affect and Self-Esteem in Early Adolescence: Correlates of Mean Levels and Within-Person Variability
Bibliographic record
Abstract
Emotions and self-esteem are critical components of well-being and adaptation during adolescence. People differ in their average levels of affect and self-esteem, as well as in how much their affect and self-esteem fluctuate from moment to moment. Fluctuations in affect in particular have not been extensively examined in relation to adolescent-relevant variables. The present study investigates internalizing symptoms, social functioning, and overt and relational aggression as correlates of average levels and within-person variability in daily positive and negative affect (PA and NA) and self-esteem. Crucially, unique association were examined controlling for the other variables. Early adolescents (mean age 10.8 years, N = 94) completed daily diaries across four days on PA, NA, and self-esteem. They also completed general questionnaires, as did peers. Some key findings were that more internalizing symptoms were significantly associated with more variability in NA. The importance of peer relationships for adolescents’ daily mean levels of PA and NA were shown. Peer-perceived social functioning was associated with less fluctuations in self-esteem. Some unexpected, non-significant, findings for aggression appeared. Finally, higher mean NA were associated with more NA fluctuations, whereas higher mean PA and self-esteem were associated with less fluctuations.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".