A Coordinated Analysis of Big-Five Trait Change Across 16 Longitudinal Samples
Bibliographic record
Abstract
This study assessed change in the Big Five personality traits. We conducted a coordinated integrative data analysis (IDA) using data from 16 studies including over 60,000 respondents to examine trajectories of change in the traits of neuroticism, extraversion, openness, conscientiousness, and agreeableness. Coordinating models across multiple study sites, we fit nearly identical multi-level linear growth curve models to assess and compare the extent of trait change over time. Quadratic change was assessed in 8 studies with four or more measurement occasions. Across studies, the linear trajectory models revealed stability for agreeableness and decreases for the other four five traits. The non-linear trajectories suggest a U-shaped curve for neuroticism, and an inverted-U for extraversion. Meta-analytic summaries indicate that the fixed effects are heterogeneous, and that the variability in traits is partially explained by baseline age and country of origin. We conclude from our study that neuroticism, extraversion, conscientiousness, and openness go down over time, while agreeableness remains relatively stable.
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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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".