What's interpersonal in interpersonal perception? The role of target's attachment in the accuracy of perception
Bibliographic record
Abstract
OBJECTIVE: We examined the influence of attachment orientation on the accuracy of perception of negative affect in close relationships. We hypothesized that tracking accuracy of perceiving negative affect (a) would be lower among perceivers and targets with higher attachment avoidance and (b) would be lowest when both the target and perceiver were high on attachment avoidance. Tracking accuracy would be (c) higher among perceivers and targets with higher attachment anxiety and (d) highest when both the target and perceiver were high on attachment anxiety. METHOD: We collected data from 92 couples who reported their negative affect and perception of their partner's negative affect in interactions with each other on 20 days. RESULTS: Results supported the hypotheses for attachment avoidance and tracking accuracy. Tracking accuracy of perceived negative affect was low when the target was high on attachment avoidance; accuracy was lowest when both the target and the perceiver were high on attachment avoidance. CONCLUSIONS: Lower "readability" of high avoidantly attached targets' emotions may inhibit intimacy and sensitive responding, which thereby may contribute to poor relationship outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".