Assessing the Psychometric Properties of the Partner Version of the Psychological Distance Scaling Task
Bibliographic record
Abstract
ABSTRACT The Psychological Distance Scaling Task (PDST), originally developed to assess self‐schema structures, has recently been adapted to assess partner‐schema structures (PSS, i.e., the degree of interconnectedness in one's beliefs about their romantic partner). However, the psychometric properties of the partner version of the PDST have yet to be assessed. Across four studies ( N = 1134), we tested whether PSS (1) were associated with relationship and, to a lesser degree, personal well‐being, (2) offered predictive utility compared to self‐schema structures, and (3) represented a distinct construct from attachment orientations. PSS were correlated with relationship well‐being indices (i.e., relationship commitment, adjustment, satisfaction, quality, as well as causal and responsibility attributions) and, to a lesser extent, personal well‐being indices (i.e., depression, anxiety, and stress), supporting its convergent validity. Hierarchical regression models revealed that, generally, PSS adds predictive utility to relationship but not personal well‐being after controlling for self‐schema structures. Finally, PSS were weakly correlated with attachment orientations and explained additional variance in relationship well‐being above and beyond attachment, supporting its divergent validity. We conclude that the partner version of the PDST is a useful tool for assessing partner schema structures.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".