Categorizing at the group‐level in response to intragroup social comparisons: a self‐categorization theory integration of self‐evaluation and social identity motives
Bibliographic record
Abstract
Abstract Two experiments examined how people respond to upward social comparisons in terms of the extent to which they categorize the self and the source of comparison within the same social group. Self‐evaluation maintenance theory (SEM) suggests that upward ingroup comparisons can lead to the rejection of a shared categorization, because shared categorization makes the comparison more meaningful and threatening. In contrast, social identity theory (SIT) suggests that upward ingroup comparisons can lead to the acceptance of shared categorization because a high‐performing ingroup member enhances the ingroup identity. We attempted to resolve these differing predictions using self‐categorization theory, arguing that SEM applies to contexts that make salient one's personal identity, and SIT applies to contexts that make collective identity salient. Consistent with this perspective, the level of identity activated in context moderated the effect of an upward ingroup comparison on the acceptance of shared social categorization. Copyright © 2006 John Wiley & Sons, Ltd.
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.
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 | 0.013 | 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 | 0.001 | 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 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".