How happy are married people? Psychological indicators of marital satisfaction of married men and women in Gauteng Province, South Africa
Bibliographic record
Abstract
The aims of this paper were to first establish the difference in scores of men and women on marital satisfaction and other psychological variables such as communication, alexithymia and psychological wellbeing and secondly, to establish whether the study variables - including gender, communication, alexithymia and psychological wellbeing will predict marital satisfaction. Based on a cross-sectional design, data was collected from a random sample of 500 married men and women with mean age of 37 years (SD = 8.98). Results of the study show that there were significant differences between men and women on three of the four subscales of the marital satisfaction scale: dyadic consensus, dyadic satisfaction and affectional expression with women scoring higher than men; there was also a significant difference between men and women on only one subscale (externally oriented thinking) of the alexithymia scale with men reporting more on externally oriented thinking than women; On psychological wellbeing, two of the subscales were statistically significant: environmental mastery with men scoring higher and self-acceptance with women scoring higher than men. Variables such as dyadic cohesion (marital satisfaction), DDF and DIF (alexithymia), verbal and non-verbal (communication) and autonomy, personal growth and positive relations (psychological wellbeing) were not significant between males and females. All three psychological variables (gender, communication, alexithymia and psychological wellbeing significantly predicted marital satisfaction and sex difference (model 1) difficulty in identifying feelings (model 2), verbal communication (model 3) and positive relations (model 4) were significant predictors of marital satisfaction. Recommendations were made in light of the findings of the study.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".