Everyday acts of kindness predict greater well‐being during the transition to university
Bibliographic record
Abstract
Abstract From becoming a teenager to starting university, life transitions are an inevitable part of human existence. While exciting, life transitions can be stressful because they involve changes in identity, routine, and expectations. What can support people during this period of change? Informed by past research demonstrating the emotional benefits of prosocial behavior, we examined whether everyday acts of prosociality might predict well‐being during a life transition using a pre‐registered 6‐week diary study conducted with students starting university ( N = 193; 1544 observations). Consistent with pre‐registered hypotheses, participants experienced higher well‐being on scales capturing happiness, flourishing, thriving, optimism, resilience, anxiety and loneliness during weeks in which they completed more prosocial acts than their personal average. This research extends our understanding of the relationship between prosociality and well‐being to new theoretically relevant contexts, including extended, multi‐faceted personal stressors, and suggests that one potentially useful route to well‐being during life transitions could be helping others.
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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 | 0.000 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".