Principles and problems of policy implementation reconsiderations for effective secondary school administration
Bibliographic record
Abstract
Policy implementation has presented the Nigerian educational system with countless obstacles cum problems. This research explored the principles and problems of policy implementation reconsiderations for effective secondary school administration. The study adopted a descriptive research design. The study population was 286 principals. The study sample was 229 principals drawn through a simple random sampling, representing 80% of the population. An instrument, principles and problems of policy implementation for effective secondary school administration was utilized for data collection. Cronbach alpha established a reliability coefficient of 0.89. Mean and standard deviation were used for data collection, while a t-test was utilized to test the hypotheses at a 0.05 significance level. The researchers found that the principles of policy implementation for effective secondary school administration are founded on ensuring a positive and clear policy statement, flexibility in the policy statement, fact-based policy statement, effectiveness in policy statement communication, openness to review, and properly documented in writing. It was recommended that school principals provide copies of the school policy to all the teachers. The principals should not be subjective in implementing policy for effective school administration. The implication of the study is that principals should adopt effective principles for policy implementation.
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 | 0.148 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.007 | 0.017 |
| 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".