The Capital it Takes to Reveal Your True Self
Bibliographic record
Abstract
Accurately expressing one’s unique personality in first impressions generally feels good (Mignault et al., 2022) and promotes positive social interactions (Human et al., 2020). However, people from higher socioeconomic status could have a privileged access to making accurate first impressions. Indeed, childhood home income relates to greater self-confidence and social skills (Hosokawa & Katsura, 2017; Li et al., 2018), characteristics which could foster accurate personality expression. Therefore, could household income in childhood relate to being accurately perceived in adulthood? To test this question, we conducted two naturalistic “speed-networking style” getting-acquainted studies, one exploratory in-person study (N=863; NDyads=4608) and one pre-registered videoconferencing study (N=879; NDyads=4990). Across studies, childhood home income related to accurate personality expression specifically for extraverts, potentially because extraverts generally make more personality cues available. Overall, childhood home income may promote accurate self-expression for those who provide ample information to others, likely leading to smoother and more positive interactions.
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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 | 0.003 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".