Bibliographic record
Abstract
Human Capital has been in recent times recognized globally as one factor that is responsible for the growth and wealth of many nations and States.However inspite of the increased awareness of individuals and government on the urgent need for increased patronage of Human Capital Development.Some governments are still yet to channel resources on Human Capital Development.This study therefore, seeks to examine the extent to which Delta State have channeled her resources into Human Capital Development.This study is necessary because most States and countries of the World are heavily investing in Human Capital development, while others are yet to take advantage of this.This study is necessary because Delta State is one of the oil producing States in Nigeria, and by this receives huge allocation from the Federal government.However, Delta State is blessed with huge financial, material and human resources.Three research questions guided this study they include: What are the contributions made by the Delta State Ministry of Education on Human Capital Development between 2007 and 2013?This study seeks to address this question using documentary sources.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.996 | 0.997 |
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; both teacher heads 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".