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Record W2770019720

Treasury Management Policy and Improvement in Revenue Base in Nigeria

2017· article· en· W2770019720 on OpenAlexvenueno aff
Wisdom Okere, Ogundana Oyebisi M, Imeokparia Lawrence A, Njogo Bibiana O

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEuropean Monetary and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsTreasuryRevenueRevenue centerGovernment revenueGovernment (linguistics)BusinessFinanceState (computer science)EconomicsPublic economicsEconomic policyPolitical scienceComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Recent decreases experienced in the federal government level of revenue generation have brought about an urgent need to improve the national revenue base through an effective and efficient Treasury Management. This revenue generation decrease at the Federal level would invariably affect the state and local government since certain percentage of their revenue is derived from the federation account. As a result of this decline in government revenue, the Federal Government is compelled to pull funds from the excess crude account and a continuous pull from this account would bring about amongst other consequences a drastic reduction in the country’s foreign reserve. To avoid such problems, there is the need for a proper Treasury Management Policy and Practice in the Nigerian System at all levels of Government.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.238
Teacher spread0.208 · 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 designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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