The influence of the mothers job on the psychological state of preschool childrenin Saudi Arabia
Bibliographic record
Abstract
Background: Children during their early developmental years face several cognitive and behavioral effects that are the result of their mother work. Objectives: To assess the relationship between mothersjob and psychological state of their preschool-age children at Sakaka City in Saudi Arabia, and to compare mothers job type with the degree of loneliness feeling of their children. Design: A descriptive survey design was used. Sample: A convenient purposeful sample of 120 working mothers of different careers and their preschool-age children aged from (2-6 years). Tools included 1. A structured questionnaire developed by the researcher 2. Likert scale for preschool-age children's loneliness feeling. Results: indicated that the mothers age ranged between 31-40 years are more than a quarter (35.8%), and rest are between (20-30 years), 89.5% of them have a university education. The degree of mothers work effect on their young children feeling of loneliness was 43.40± 1.095 very affects. On the other hand, 43.25± 3.56 was does not affect at all. Conclusions: It was concluded that there was a relationship between mothers job and loneliness feelings of their preschool age children. The loneliness feeling for children increases related to the type of mother work where school teachers were the most mothers career associated with a high sense of loneliness among their children.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".