Behavioural Problems of Juvenile Street Hawkers in Uyo Metropolis, Nigeria
Bibliographic record
Abstract
The study sought the opinions of Faculty of Education Students of University of Uyo on the behavioural problems of juvenile street hawkers in Uyo metropolis. Five research hypotheses were formulated to guide the study. This cross-sectional survey employed multi-stage random sampling technique in selecting 200 regular undergraduate students in the Education Faculty of the University of Uyo for the study. The Juvenile Street Hawkers Opinioniare (JUVSHO) developed by the researchers was used in data collection. The hypotheses were tested using chi square statistic at p≤.05 level of significance and appropriate degrees of freedom. Results indicate that juvenile street hawkers develop maladjusted patterns of behaviour, which in turn impair their academic, moral, social, physical, and psychological growth and development thus affecting their future negatively. Based on these findings, it was recommended that government should provide free basic education, improve workers remuneration, provide academic grants and aids to economically disadvantaged parents, and create jobs for unemployed parents, inter alia, in order to keep children from hawking under the guise of subsisting family income at the expense of their total development. Also, the implications of these findings for counselling psychologists in the school system were given.
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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 | 0.001 |
| 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 | 0.000 | 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".