Age Differences at Marriage Between Couples and the Risk of Divorce in Amassoma Community, Bayelsa State, Nigeria
Bibliographic record
Abstract
This study aimed to examine whether age differences between married couples were a determinant in marital instability among married people in Amassoma community, Bayelsa State, Nigeria. A descriptive survey design was used as the research frame for the study. Purposive sampling techniques were used to sample 22 respondents for the study. Three hypotheses were formulated to keep the study in focus. The results of the study revealed that age differences among marriage couples account for the high rate of divorce in our study area. Husband-older couples were significantly more dissatisfied and experience high rate of divorce than wife older, and same-age marriages. The study gives valuable insight to the future use of couple therapist in society. Family therapists can work with couples for nurturing their intimacy thereby control and handling couples conflicts by knowing about spouses differences based on Gender and age differences.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".