Commitment insurance: Compensating for the autonomy costs of interdependence in close relationships.
Bibliographic record
Abstract
A model of the commitment-insurance system is proposed to examine how low and high self-esteem people cope with the costs interdependence imposes on autonomous goal pursuits. In this system, autonomy costs automatically activate compensatory cognitive processes that attach greater value to the partner. Greater partner valuing compels greater responsiveness to the partner's needs. Two experiments and a daily diary study of newlyweds supported the model. Autonomy costs automatically activate more positive implicit evaluations of the partner. On explicit measures of positive illusions, high self-esteem people continue to compensate for costs. However, cost-primed low self-esteem people correct and override their positive implicit sentiments when they have the opportunity to do so. Such corrections put the marriages of low self-esteem people at risk: Failing to compensate for costs predicted declines in satisfaction over a 1-year period.
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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".