Seeing you, seeing me: Links between perceived commitment, metaperceptions, and relationship well‐being
Bibliographic record
Abstract
Abstract Are perceiver's impressions of target's commitment associated with the target's relationship experience? Could target's metaperceptions (i.e., target's beliefs about the perceiver's impressions of the target) help explain why? In the present dyadic study ( N = 206; N couples = 103), we found that perceiver's impressions of target's commitment was positively related to target's relationship well‐being, and target's metaperceptions helped to account for this link. Additional analyses disentangled the roles of accuracy and bias of metaperceptions. On average, people underestimated their partners' impressions of commitment, and this negative mean‐level bias was related to lower relationship well‐being. Overall, the present results shed light on the potential implications of metaperceptions for relational 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".