Factors Responsible for Husband Battering as Expressed by Married Adults in Lagos State, Nigeria
Bibliographic record
Abstract
Several factors have emerged as a major concern on the factors responsible for husband battering as expressed by married adults in Lagos State. The study examined factors responsible for husband battering as expressed by married adults in Lagos State. The study also examined the influence of moderating variables of gender, employment status, age in marriage and educational qualification. Descriptive survey designed was adopted. The population consists of married adults in Lagos State. The sample consists of two hundred married adults in Lagos State and was selected using a proportional and simple random sampling techniques. One research question was raised and four null hypotheses were also postulated respectively. Data were collected using a researcher-designed questionnaire tagged “Factors Responsible for Husband Battering Questionnaire (FRHBQ)”. Data analysis was done using t-test and Analysis of Variance (ANOVA) at 0.05 level of significance. Finding revealed that poor communication between couples is the most causality of husband battering among married adults in Lagos State. The findings of the study also revealed that there was a significant difference in the perception of respondents on factors responsible for husband battering on the basis of employment status and no significant difference in respondents’ perception on the basis of gender, age in marriage and educational qualification. Based on the findings of this study, it was recommended that couple should jealous moderately and avoids envying their partner on irrelevant issues so that husband battering could be prevented in the home.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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; 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".