Humility Throughout the Lifespan and a Global Pandemic: Evidence From a Large‐Scale Cross‐Sectional Study
Bibliographic record
Abstract
OBJECTIVE: We provide a fine-grained portrait of age-graded differences in Humility across the lifespan. Specifically, we shed light on year-by-year differences and explore differences-in-differences in the wake of the COVID pandemic. METHODS: We used large-scale cross-sectional data (n = 2,025,004) and employed multigroup confirmatory factor analysis, ANOVAs, and multilevel modeling to examine mean-score differences in Humility from age 10 to 70 across the entire sample, and for temporal (pre-COVID, COVID) and geographical (9 countries, 6 US states) subsamples. RESULTS: Across cultures and geographies, Humility mean scores were lowest in late childhood and rose steadily thereafter. They reached their highest levels in late adulthood and exhibited more erratic patterns around retirement age. In the overall and pre-COVID samples, mean-score differences were most pronounced during the transition from early to middle adulthood. In the COVID sample, similar patterns emerged, though we observed generally higher Humility scores, pronounced adolescent disruption, and the biggest differences between early and middle adulthood. CONCLUSIONS: Age-graded trends in Humility aligned fully with some established patterns of personality trait development (i.e., psychological maturation, maturation reversal) and partially with others (i.e., disruption hypothesis). Moreover, the COVID analyses provide preliminary insights into the potential effects of the pandemic on personality development trajectories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".