Types of High Self-Esteem and Prejudice: How Implicit Self-Esteem Relates to Ethnic Discrimination Among High Explicit Self-Esteem Individuals
Bibliographic record
Abstract
There is increasing recognition that high self-esteem is heterogeneous. Recent research suggests that individuals who report having high self-esteem (i.e., have high explicit self-esteem) behave more defensively to the extent that they have relatively low implicit self-esteem. The current studies test whether individuals with high explicit self-esteem are more likely to discriminate ethnically, as a defensive technique, to the extent that they have relatively low implicit self-esteem. The results support this prediction. Among participants with high explicit self-esteem, all of whom were threatened by negative performance feedback, those with relatively low implicit self-esteem recommended a more severe punishment for a Native, but not a White, student who started a fist-fight. In Study 2, this pattern was not apparent for participants with relatively low explicit self-esteem.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".