Early life experiences and adult orientation to promote good in 22 countries
Bibliographic record
Abstract
Prior research suggests associations between character involving an orientation to promote good (i.e., a disposition to take actions that contribute to the good of oneself and others) and improved well-being outcomes. However, less is known about childhood factors that may lead to a greater disposition to promote good. This study used data from 202,898 adults in 22 countries to evaluate childhood antecedents of an orientation to promote good. We examined the associations between retrospectively reported childhood experiences and adult disposition to promote good in each country individually, and cross-nationally by meta-analytically pooling results across countries. The pooled results suggest that childhood experiences including having positive relationships with parents, higher subjective financial status, better childhood self-rated health, frequent religious service attendance, an earlier year of birth, and being female were associated with a greater orientation to promote good in adulthood. Conversely, the childhood experiences of abuse and feeling like an outsider in the family were associated with lower levels of promoting good. In country-specific analyses, the direction and strength of these associations differed by country, indicating diverse societal influences. This study provides a valuable foundation for future investigations into the influence of childhood experiences on character across cultures and national contexts.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".