Acceptance is in the eye of the beholder: Self-esteem and motivated perceptions of acceptance from the opposite sex.
Bibliographic record
Abstract
Social risk elicits self-esteem differences in signature social motivations and behaviors during the relationship-initiation process. In particular, the present research tested the hypothesis that lower self-esteem individuals' (LSEs) motivation to avoid rejection leads them to self-protectively underestimate acceptance from potential romantic partners, whereas higher self-esteem individuals' (HSEs) motivation to promote new relationships leads them to overestimate acceptance. The results of 5 experiments supported these predictions. Social risk increased activation of avoidance goals for LSEs on a word-recall task but increased activation of approach goals for HSEs, as evidenced by their increased use of likeable behaviors. Consistent with these patterns of goal activation, even though actual acceptance cues were held constant across all participants, social risk decreased the amount of acceptance that LSEs perceived from their interaction partner but increased the amount of acceptance that HSEs perceived from their interaction partner. It is important to note that such self-esteem differences in avoidance goals, approach behaviors, and perceptions of acceptance were completely eliminated when social risk was removed.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".