Perceived Regard Explains Self- Esteem Differences in Expressivity
Bibliographic record
Abstract
Baumeister, Tice, and Hutton proposed that individuals with low self-esteem (LSEs) adopt a more cautious, self-protective self-presentational style than individuals with high self-esteem (HSEs). The authors predicted that LSEs' self-protectiveness leads them to be less expressive--less revealing of their thoughts and feelings--with others than HSEs, and that this self-esteem difference is mediated by their perceptions of the interaction partner's regard for them. Two correlational studies supported these predictions (Studies 1 and 2). Moreover, LSEs became more expressive when their perceived regard was experimentally heightened--when they imagined speaking to someone who was unconditionally accepting rather than judgmental (Study 3) and when their perceptions of regard were increased through Marigold, Holmes, and Ross's compliment-reframing task (Study 4). These findings suggest that LSEs' expressiveness can be heightened through interventions that reduce their concerns about social acceptance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".