Factor Structure of the Dyadic Adjustment Scale
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. The Dyadic Adjustment Scale (DAS) is one of the most widely used instruments for measuring relationship quality. Considering the discrepancies across studies regarding the relationship of the underlying constructs of the DAS, the aim of the present study was to examine the factor structure of the scale by applying bifactor models using confirmatory factor analytic (CFA) and exploratory structural equation modeling (ESEM) approaches. The sample consisted of 483 couples recruited in Hungary. The analysis revealed that the bifactor-ESEM yielded the best fit to the data (CFI = .90, RMSEA = .05, WRMR = .88). Further, strict invariance between the sexes was observed for this model. Omega hierarchical coefficients indicated outstanding reliability for the general factor (.86), acceptable estimates for the Dyadic Consensus (.60) and Cohesion (.57) subdomains, but poor reliability for the Dyadic Satisfaction (.22) and Affectional Expression (.36) factors; suggesting that the individual interpretation of these latter two subconstructs must be made with caution.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it