The regulatory function of self-esteem: Testing the epistemic and acceptance signaling systems.
Bibliographic record
Abstract
The authors draw on sociometer theory (e.g., Leary, 2004) and self-verification theory (e.g., Swann, 1997) to propose an expanded model of the regulatory function of self-esteem. The model suggests that people not only possess an acceptance signaling system that indicates whether relational value is high or low but also possess an epistemic signaling system that indicates whether social feedback is consistent or inconsistent with chronic perceived relational value (i.e., global self-esteem). One correlational study and 5 experiments, with diverse operationalizations of social feedback, demonstrated that the epistemic signaling system responds to self-esteem consistent or inconsistent relational-value feedback with increases or deceases in epistemic certainty. Moreover, Studies 3-6 demonstrated that the acceptance and epistemic signaling systems respond uniquely to social feedback. Finally, Studies 5 and 6 provide evidence that the epistemic signaling system is part of a broader self-regulatory system: Self-esteem inconsistent feedback caused cognitive efforts to decrease the discrepancy between self-views and feedback and caused depleted self-regulatory capacity on a subsequent self-control task.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".