Investment in Education for The Nigerian Economic Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines investment in education for economic development of Nigeria. Education has been recognized globally as a veritable and strategic venture pivotal to economic transformation of any nation. The study made use of secondary data sourced from Ministry of Education, National Universities Commission (NUC) and Tertiary Education Trust Fund (TETFUND) and an Ordinary Least Square (OLS) regression method was used to analyze the data obtained to show the relationship between enrolments and funding. The result shows that the education sector contribute significantly to economic development as measured by the Gross Domestic Product although the sector is still underfunded most especially the basic and senior secondary levels in view of geometric increase in yearly enrollments and poor infrastructural facilities. The study recommends that the government at all levels should invest more in education and also collaborate with private sector through Private Public Partnership (PPP) initiative to accumulate the much needed funding that will pave way for technological development. It will also guide against brain-drains and significantly alleviate overdependence on aids from the developed nations and educational organizations.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it