Target adjustment and self-other agreement: Utilizing trait observability to disentangle judgeability and self-knowledge.
Bibliographic record
Abstract
Are well-adjusted individuals good targets or accurate self-judges? Across two round-robin studies, the current research first demonstrates that well-adjusted individuals' personalities are viewed with greater distinctive self-other agreement by new acquaintances. Is this enhanced self-other agreement a function of greater judgeability, improving others' ability to form an accurate impression? Or is it a function of greater self-knowledge, having a more accurate impression about oneself? By examining the relationship between psychological adjustment and self-other agreement as a function of trait observability, it becomes clear that psychological adjustment fosters self-other agreement through judgeability more so than through self-knowledge. Specifically, well-adjusted individuals provide new acquaintances with greater information regarding their less observable traits, enhancing others' knowledge and thus distinctive self-other agreement. This effect was replicated with close informant-other agreement, indicating that the well-adjusted individual's tendency to make his or her less visible traits more accessible to others allows those who just met the target to agree better with people who know the target well. In sum, although well-adjusted individuals are in part good self-judges, it is their greater judgeability that seems most critical in enhancing self-other agreement in first impressions.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".