You Don’t Really Love Me, Do You? Negative Effects of Imagine-Other Perspective-Taking on Lower Self-Esteem Individuals’ Relationship Well-Being
Bibliographic record
Abstract
Two studies demonstrated that active efforts to appreciate a romantic partner's unique point of view (imagine-other perspective-taking) lead individuals lower in self-esteem (LSEs) to feel less loved by their partner and less satisfied with their relationship as a result. These effects were evident regardless of whether individuals' perspective-taking efforts involved reflecting specifically on a disagreement with their partner (Study 2) or not (Study 1). The studies thus identify a new path through which perspective-taking efforts can detract from relational well-being, one to which LSEs are uniquely vulnerable. Results from an open-ended thought-listing task administered in Study 2 confirmed that increased cognitive energy LSEs devoted to drawing (negative) metaperceptual inferences about their partner's evaluation of them contributed to the negative effect of imagine-other perspective-taking on their perceived regard. No such effects were evident for individuals higher in self-esteem, and imagine-self perspective-taking instead exerted a general positive influence on individuals' evaluations of their partner.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".