Short-term dynamics of pride and state self-esteem change during the university-to-work transition
Bibliographic record
Abstract
Young adults differ in their self-esteem change during the university-to-work transition. The short-term processes (such as state changes) which are related to individual variability in change are not yet fully understood. In this pre-registered study, we examined experiences of pride as an emotional process underlying state self-esteem change in a sample of 232 Dutch master students over 8 months across their university-to-work transition. We used dynamic and multilevel structural equation models to analyze three waves of 14-day experience sampling data, examining momentary and daily associations between pride and state self-esteem on the within-person level. We examined correlated change in pride and state self-esteem, and the extent to which pride predicted variability in state self-esteem change. Results indicated positive within-person associations and considerable individual differences in pride–state self-esteem associations across moments and days. Across months, changes in pride and state self-esteem were positively correlated, but pride before graduation did not predict variability in later state self-esteem change. Pride–state self-esteem associations remained robust after accounting for feelings of joy, transitional valence, and timing of the transition. Findings indicated that pride uniquely predicted state self-esteem change during the education-to-work transition, which suggests that pride is a key emotion underlying self-esteem change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".