Managing motivational conflict: How self-esteem and executive resources influence self-regulatory responses to risk.
Bibliographic record
Abstract
This article explores how self-esteem and executive resources interact to determine responses to motivational conflict. One correlational and 3 experimental studies investigated the hypothesis that high and low self-esteem people undertake different self-regulatory strategies in "risky" situations that afford opportunity to pursue competing goals and that carrying out these strategies requires executive resources. When such resources are available, high self-esteem people respond to risk by prioritizing and pursuing approach goals, whereas low self-esteem people prioritize avoidance goals. However, self-esteem does not influence responses to risk when executive resources are impaired. In these studies, risk was operationalized by exposing participants to a relationship threat (Studies 1 and 2), by using participants' self-reported marital conflict (Study 3), and by threatening academic competence (Study 4). Executive resources were operationalized as cognitive load (Studies 1 and 2), working memory capacity (Study 3), and resource depletion (Study 4). When executive resources were ample, high self-esteem people responded to interpersonal risk by making more positive relationship evaluations (Studies 1, 2, and 3) and making more risky social comparisons following a personal failure (Study 4) than did low self-esteem people. Self-esteem did not predict participants' responses when executive resources were impaired or when risk was absent. The regulatory function of self-esteem may be more resource-dependent than has been previously theorized.
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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 | 0.002 | 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) | 0.000 | 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".