Half Empty <i>and</i> Half Full? Biased Perceptions of Compassionate Love and Effects of Dyadic Complementarity
Bibliographic record
Abstract
The prevailing theory on relationship judgments for interaction attributes suggests individuals tend to underestimate a romantic partner’s expressions of compassionate love and that such underestimation is beneficial for the relationship. Yet, limited research has incorporated dyadic perspectives to assess how biased perceptions are associated with both partners’ outcomes. In two daily studies of couples, we used distinct analytical approaches (Truth and Bias Model; Dyadic Response Surface Analysis) to inform perspectives on how biased perceptions are interrelated and predict relationship satisfaction. Consistent with prior research, people demonstrated an underestimation bias. However, there were differential effects of biased perceptions for actors versus partners: Underestimation predicted lower actor satisfaction but generally higher satisfaction for partners. Furthermore, we find evidence for complementarity effects: partners’ directional biases were inversely related, and couples were more satisfied when partners had opposing patterns of directional bias. Findings help integrate theoretical perspectives on the adaptive role of biased relationship perceptions.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".