Validity of three measures of communication for predicting relationship adjustment and stability among a sample of young couples.
Bibliographic record
Abstract
The goal of this study was to examine whether data from 3 different measures of communication (i.e., self-report, quasi-observational, and observational) can predict relationship adjustment and stability 1 year later when used conjointly in a sample of 62 young couples. The 3 measures of communication were the Communication Skills Test--Revised (CST-R), the Communication Box (CB), and the Demand/Withdraw Pattern Questionnaire (DWPQ). Through hierarchical multiple regression analyses, results revealed that the CST-R and the DWPQ predict both genders' relationship adjustment 1 year later when used conjointly. Logistic regression analyses revealed that none of the measures of communication significantly predicted relationship stability. In conclusion, the combination of the CST-R and the DWPQ appears to be useful for longitudinally predicting relationship adjustment.
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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 | 0.002 | 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 | 0.000 | 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".