Social Variables and Dropout Tendencies among Secondary School Students in Ikom Education Zone, Cross River State, Nigeria
Bibliographic record
Abstract
This study was on social variables and dropout tendencies among secondary school students in Ikom education zone, Cross River State, Nigeria. The social variables considered were substance abuse, family type and teacher/students relationship. Out of population of 7228 students, sample of 506 students were randomly selected for the study. A survey design was adopted. The instrument used for data collection was questionnaires titled ‘Social Variables and Dropout Tendencies Questionnaire’. Three hypotheses were formulated and tested at .05 level of significant. The statistical tools used are Pearson Product Moment Correlation Coefficient and Independent t-test. The results showed that there was significant relationship between (i) substance abuse and dropout tendencies. (ii) family type and dropout tendencies (iii) teacher/student relationship and dropout tendencies. The results were discussed and the researchers recommended that: (i) students be monitored and counseled against substance abuse both at home and in school. (ii) parents should for the sake of their children stay together and train them. (iii) teachers should create conducive and favourable environment for the students to learn.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".