The relation between belief in a just world and early processing of deserved and undeserved outcomes: An ERP study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We used event-related potentials (ERPs) to examine how quickly people in general, and certain people in particular, process deservingness-relevant information. Female university students completed individual difference measures, including individual differences in the belief in a just world (BJW), a belief that people get what they deserve. They then read stories in which an outcome was deserved, undeserved, or neither deserved nor undeserved (i.e., “neutral”) while their ERPs were recorded with scalp electrodes. We found no overall differentiation between early ERP responses (<300 ms post-stimulus onset) to deserved, undeserved, and neutral outcomes. However, BJW correlated with the difference between early ERP responses to these forms of information (rs from |.44| to |.61|; ps from .018 to < .001). The early nature of our effects (e.g., 96 ms after stimulus onset) suggests individual differences in socially-relevant information processing that begins before conscious evaluation of the stimuli. Potential underlying processes include automatic attention to schema-relevant information and to unexpected (and therefore salient) information and automatic processing of belief-consistent information. Our research underscores the importance of the concept of deservingness in human information processing as well as the utility of ERP technology and robust statistical analyses in investigations of complex social stimuli.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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