MétaCan
Menu
Back to cohort
Record W4411656959 · doi:10.51847/dabqxvhyqs

10.51847/DabqXvhyqs

2000· article· en· W4411656959 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicUnemployment and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryDeltaHuman capitalState (computer science)Economic growthPolitical scienceDevelopment economicsEconomicsEngineeringComputer scienceLaw

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.794
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9960.997

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.

Opus teacher head0.014
GPT teacher head0.157
Teacher spread0.142 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicUnemployment and Economic GrowthFrench-language works237,207