Principals’ Perception of Misconduct among Secondary School Teachers in Delta State: Implications for Counselling Practice
Bibliographic record
Abstract
This study investigated Principals’ Perception of misconduct among Secondary School teachers in Delta State. Four research questions and four hypotheses were formulated to guide the study. The instrument used for collection of data was tagged “Principals’ Perception of Teachers Misconduct Questionnaire” (PPOTMQ). For content validity, the instrument was given to some lecturers in the Department of Guidance & Counselling who scrutinized it and made some corrections. The test-retest method of reliability was employed and the co-efficient of 0.72 was obtained. The sample consisted of 100 principals. The t-test statistics was employed to test the hypotheses at 0.05 level of significance. Results of the study revealed that absenteeism, lateness, truancy and poor quality teaching were perceived by principals as forms of misconduct in public secondary schools. Recommendations that were proffered include; monitoring teams should be put in place by school authorities to supervise teachers’ attendance in class as well as their teaching, inspectors from the Post-Primary Education Board should pay regular unscheduled visits to secondary schools to act as a check on teachers’ absenteeism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".