Bibliographic record
Abstract
Nigeria independence in 1960 had brought a reactive governance targeting provision of manpower to satisfy limited governmental or white-collar jobs from parastatals, ministries and industries which were mostly under government control.Practice of entrepreneurship which led to self-sustenance, self-reliance and self-esteem before independence was neglected, and not even considered in the schools' curricula.A reflection of Nigerian style of entrepreneurial system of olden days should be seen in the curricula of Nigerian educational system to address employment challenges.The development will provide enablement for business development with due consideration of cultures and religions.In Nigeria, success of entrepreneurship practice is divided into four, namely golden age (up to 1970), trial age (1970-till date), sustainable age and consolidation age, indicating degree of success attainable.For system sustainability, Nigeria's educational system should be restructured to reflect the technical and entrepreneurial skills needed to drive home national economy.Creation of educationally-based entrepreneurship system and provision of enablement for school leavers to take up businesses after graduation will consolidate employment stability of the nation.Suggestions were provided to enable movement from schools (after graduation) to shops, industries, or farms without waiting for government-based job.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.971 | 0.965 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".