Socioeconomic Status and Meta-Perceptions: How Markers of Culture and Rank Predict Beliefs About How Others See Us
Bibliographic record
Abstract
How does a person’s socioeconomic status (SES) relate to how she thinks others see her? Seventeen studies (eight pre-registered; three reported in-text and 14 replications in supplemental online material [SOM], total N = 6,124) found that people with low SES believe others see them as colder and less competent than those with high SES. The SES difference in meta-perceptions was explained by people’s self-regard and self-presentation expectations. Moreover, lower SES people’s more negative meta-perceptions were not warranted: Those with lower SES were not seen more negatively, and were less accurate in guessing how others saw them. They also had important consequences: People with lower SES blamed themselves more for negative feedback about their warmth and competence. Internal meta-analyses suggested this effect was larger and more consistent for current socioeconomic rank than cultural background.
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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 | 0.018 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.007 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".