Relationship between the Belief System and Emotional Well-Being of Single Mothers
Bibliographic record
Abstract
<p>This study aimed to identify the relationship between the belief system and emotional well-being of single mothers in Kluang, Johor. This study involved 58 respondents using the purposive sampling technique. Questionnaires were used to identify the emotional well-being and respondents' belief system. Data were analysed using Statistical Package for the Social Science (SPSS 19.0). Descriptive statistics in the form of percentage, mean, and inferential statistics, namely, ‘Pearson r’ correlation analysis was used to identify the relationship between single mothers’ emotions and their belief system. Results of the study found the single mothers’ emotional well-being to be moderate (M = 23:56, S.D = 6.62) and their belief system to be high (M = 37.55, S.D = 8.22). In addition, the study also showed a significant difference between the single mothers’ age, reason for becoming single mothers, occupation, number of dependent children and family members, in relation to the single mothers’ belief system and emotional well-being. However, there was no significant difference in the relationship between their level of education and belief system. The study also showed a moderate correlation between the two variables (r = 0.665, p = 0.000). Implications of the study are discussed and further research can be carried out on samples who have recently experienced a separation or divorce, to assess the short term and long term impact. </p>
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".