Parental Demographic Variables as Determinants of Knowledge of Nutritional Needs of Preschoolers in North Central Zone, Nigeria
Bibliographic record
Abstract
The general purpose of the study was to determine the influence of demographic variables of parents on knowledge and practices of nutritional needs and cognitive readiness of preschoolers in North Central Zone, Nigeria. The study adopted an ex post facto research design with a sample of 400 parents of preschool children drawn using multistage sampling procedure. Two instruments were used for data collection; “Parental Knowledge and Practices of Nutritional Needs of Preschoolers Questionnaire (PKPNNPQ) and Parental Knowledge and Practices of Cognitive Readiness of Preschoolers Questionnaire (PKPCRPQ). The instruments were validated by three experts. The reliability indices of the instruments were estimated using Cronbach’s Alpha approach. The overall reliability coefficients of PKPNNPQ and PKPCRPQ were 0.84 and 0.82 respectively. Data collected were analyzed using mean, ANOVA and t-test statistics. Mean was used to answer all the research questions, while ANOVA and t-test statistics were used to test all the null hypotheses at 0.05 level of significance. Findings revealed that parents’ occupation had significant influence on their knowledge, and practice of the nutritional needs of preschoolers while location had no significant influence. It was therefore recommended that parents in different occupations should be educated and equipped with the necessary knowledge in their workplace about the nutritional needs of preschoolers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".