The equilibrium model of relationship maintenance.
Bibliographic record
Abstract
A new equilibrium model of relationship maintenance is proposed. People can protect relationship bonds by practicing 3 threat-mitigation rules: Trying to accommodate when a partner is hurtful, ensuring mutual dependence, and resisting devaluing a partner who impedes one's personal goals. A longitudinal study of newlyweds revealed evidence for the equilibrium model, such that relationship well-being (as indexed by satisfaction and commitment) declining from its usual state predicted increased threat-mitigation; in turn, increasing threat mitigation from its usual state predicted increased relationship well-being. Longitudinal findings further revealed adaptive advantages to uncertain trust. First, the match between trust and partner-risk predicted the trajectory of threat mitigation over time. People who hesitated to trust a high-risk partner became more likely to mitigate threats over 3 years, but people who hesitated to trust a safe partner became less likely to mitigate threats. The match between threat mitigation and partner-risk also predicted when being less trusting eroded later relationship well-being. Namely, when women paired with high-risk partners became more likely to mitigate threats, being less trusting at marriage lost its capacity to erode later relationship well-being.
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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 | 0.000 |
| 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".