Electrophysiological correlates of implicit valenced self-processing in high vs. low self-esteem individuals
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Bibliographic record
Abstract
We provide the first high-temporal resolution account of the self-esteem implicit association test (IAT; Greenwald & Farnham, 2000) to highlight important similarities and differences between the cognitive processes corresponding to implicit valenced self-processing in high vs. low self-esteem individuals. We divided individuals into high and low self-esteem groups based on the Rosenberg self-esteem scale (Rosenberg, 1965) and administered the self-esteem IAT while recording electroencephalographic data. We show that the P2 captured group (high vs. low self-esteem) differences, the N250 and the late parietal positivity (LPP) captured differences corresponding to category pairing (self/positive vs. self/negative pairing), and the N1, P2, and P300-400 components captured interactions between self-esteem groups and whether the self was paired with positive or negative categories in the IAT. Overall, both high and low self-esteem groups were sensitive to the distinction between positive and negative information in relation to the self (me/negative generally displayed larger event-related potential amplitudes than me/positive), but for high self-esteem individuals, this difference was generally larger, earlier, and most pronounced over left-hemisphere electrodes. These electrophysiological differences may reflect differences in attentional resources devoted to teasing apart these two oppositely valenced associations. High self-esteem individuals appear to devote more automatic (early) attentional resources to strengthen the distinction between positively or negatively valenced information in relation to the self.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it