Perceptions of a romantic partner’s approach and avoidance motives: Accuracy, bias, and emotional cues.
Bibliographic record
Abstract
We examined tracking accuracy and bias (mean-level and projection) in people's perceptions of their romantic partner's relationship approach and avoidance motives, similarity in partners' motives, and positive and negative emotions as potential cues used to make judgments about a partner's daily motives and motives during shared activities. Using data from 2 studies, 1 using daily diaries (N = 2,158 daily reports), the other using reports of shared activities (N = 1,228 activity reports), we found evidence of tracking accuracy and projection across samples; we also found evidence of mean-level bias such that people underperceived their partner's approach (daily) and avoidance motives (daily and in shared activities). Partners had similar daily approach and avoidance motives but were not similar in their motives during shared activities. Further, our studies indicated that emotions often serve as relevant, available, and detectable cues for judging a partner's motives. The results demonstrate that accuracy and bias are both present in judgments of a romantic partner's approach and avoidance motives, and that people often, but not always, use their partner's emotions to make such judgments. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.000 |
| 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 | 0.001 |
| 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".