Social acceptance and self-esteem: Tuning the sociometer to interpersonal value.
Bibliographic record
Abstract
The authors draw on sociometer theory to propose that self-esteem is attuned to traits that garner others' acceptance, and the traits that garner acceptance depend on one's social role. Attunement of self-esteem refers to the linkage, or connection, between self-esteem and specific traits, which may be observed most clearly in the association between self-esteem and specific self-evaluations. In most roles, appearance and popularity determine acceptance, so self-esteem is most attuned to those traits. At the same time, interdependent social roles emphasize the value of communal qualities, so occupants of those roles have self-esteem that is more attuned to communal qualities than is the general norm. To avoid the biases of people's personal theories, the authors assessed attunement of self-esteem to particular traits indirectly via the correlation between self-esteem and self-ratings, cognitive accessibility measures, and an experiment involving social decision making. As hypothesized, self-esteem was generally more attuned to appearances than to communal qualities, but interdependent social roles predicted heightened attunement of self-esteem to qualities like kindness and understanding.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".