Marital Happiness of Married Couples in the U.A.E Society: A Sample from Sharjah
Bibliographic record
Abstract
The goal of this study is to examine the marital happiness of married couples in Sharjah Emirate, UAE, and its determinants. To achieve these goals, data from Family Cohesion Survey (FCS) are used; a cluster sample (1136) was randomly drawn from all local families in the Emirate of Sharjah, U.A.E.; descriptive statistics (percentages, means, and standard deviations) and analytical statistics (multiple regression) are used to analyze the data set. The results of the regression analysis reveal that there are statistically significant relation between couple's communication, education, sex, residence, self-reported health, family size, and religiosity and marital happiness of married couples. However, the analysis result reveals that family income, working status, and age are silent predictors of marital happiness.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".