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Record W1650758982 · doi:10.3968/5992

Effective Management of Tertiary Education in Nigeria as a Panacea to Good Governance and National Security

2014· article· en· W1650758982 on OpenAlexvenueno aff
Musibau Adeoye Yusuf, Festus Oluwole Afolabi

Bibliographic record

VenueHigher education of social science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsPanacea (medicine)Higher educationCorporate governanceGood governanceEconomic growthBusinessInvestment (military)Human capitalDevelopment economicsPublic relationsEconomicsPolitical scienceFinanceLaw

Abstract

fetched live from OpenAlex

Tertiary education is widely accepted in Nigeria today as a form of investment in human capital development that yields economic benefits and contributes significantly to the nation’s future wealth and development by increasing the productive and consumptive capacity of the citizens. Tertiary education equips the individual with relevant knowledge, skills and attitudinal orientation required to progress in one’s chosen career in life and contribute meaningfully to the economic growth and security of the nation, through purposeful governance. Ironically, tertiary education in Nigeria today is facing myriads of problems. Effective management of the tertiary education entails that the administrators of the tertiary institutions must identify these critical problems and harness judiciously available resources towards alleviating them. Effective management of tertiary education in Nigeria as a panacea for good governance and national security depends greatly upon the quality and quantity of all resources earmarked for this level of education, by all its stakeholders as well as prudential management of the resources.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.341
Teacher spread0.334 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations2
Published2014
Admission routes1
Has abstractyes

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