Capturing complexity in thinking requires complexity in methods
Bibliographic record
Abstract
This study tests three common assumptions in research on complex thought and wisdom: common cause of indicators, cross-situational consistency, and between-within isomorphism. Using a year-long, multi-wave study of 499 North Americans’ event-contingent reflections on autobiographical adversity, we examined intellectual humility, open-mindedness, perspective taking, and search for a compromise/conflict resolution. Network models outperformed factor models, questioning the common cause assumption. Wisdom-related features showed lower stability than personality traits and subjective well-being, challenging cross-situational consistency. Between-person and within-person associations differed, violating the isomorphism assumption. Longitudinal analyses further revealed that within-person change in self-distancing and perceived level of distress, but not other proposed moderators, were associated with within-person growth in several wisdom features three months later. These results call for a revision of approaches to studying complex thought and adversity, highlighting the importance of longitudinal research and more precise temporal claims in psychological science.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.051 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".