Lateness: A Recurrent Problem among Secondary School Students in Akoko South East Local Government Area of Ondo State Nigeria, Implications for Counselling
Bibliographic record
Abstract
The study investigated lateness as a recurrent problem among secondary school students in Akoko South East Local Government Area of Ondo State. Four hypotheses were formulated and an instrument titled “Cause of Lateness to School Questionnaire” (COLTSQ) used to gather data for the study. The instrument had a reliability coefficient of 0.78. It had content validity and language appropriateness. The researcher used two research assistants to administer 325 copies of the questionnaire on SS2 and SS3 students in the 5 public secondary schools used. 300 copies of the questionnaire were retrieved showing 92.3 percent return rate. The data collected were collated and the t-test statistics was used to test the hypotheses at 0.05 level of significance. The findings showed that there is no significant difference between male and female students in their identification of electronic media as a reason for lateness to school, there is no significant difference between students from high and low socio-economic status in their identification of broken home as a reason for lateness to school, there is no significant difference between SS2 and SS3 students in their identification of location of school as a reason for lateness to school, there is no significant difference between students in urban and rural areas in their identification of cultural background as a reason for lateness to school. One of the recommendations is that parents should put in place enforceable rules or time limit for watching television programmes at night and ensure that their children go to bed early.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".