Development and Validation of a Couples Measure of Biased Responding: The Marital Aggrandizement Scale
Bibliographic record
Abstract
More than 30 years ago, Edmonds (1967) recognized the need for a couples measure of biased responding. Like other categories of self-report instruments, marital measures are believed to be highly susceptible to distortion. In this study, we describe the development of the Marital Aggrandizement Scale (MAS). For this study, item analyses were performed on a subset of responses (n = 200). A priori inclusion criteria were applied from which a set of 18 items was selected. Three phases of validation research establish the reliability and validity of responses to the MAS among an international sample of older married adults (n = 410). The concurrent and discriminant validity of responses to this scale is demonstrated vis-à-vis separate measures of biased responding, marital satisfaction, and psychological well-being. Internal consistency was calculated as alpha = .84. Test-retest reliability was calculated as r(200) = .80 over an average interval of 15 months. The challenge remains to identify factors associated with the etiology and maintenance of this construct. Subsequent research is required to identify correlates and antecedents of marital aggrandizement across populations over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".