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Record W2283629817 · doi:10.5539/jel.v5n2p1

Internally Generated Revenue (IGR) and Effectiveness of University Administration in Nigeria

2016· article· en· W2283629817 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsBeautificationRevenueDescriptive statisticsPopulationProduct (mathematics)BusinessTransformative learningMarketingManagementBusiness administrationSociologyAccountingEconomicsPedagogyEngineeringStatisticsMathematicsDemography

Abstract

fetched live from OpenAlex

<p>The purpose of the study was mainly to identify the major sources and utilization of internally generated financial revenue by Nigerian University administrators. The population of the study consisted of all the 102 university administrators from the seventeen Federal Universities in Southern Nigeria. Descriptive statistics and Pearson Product Moment Correlation were used to analyze the research questions and hypotheses formulated for the study. The analysis revealed that commercial ventures were among the main sources of IGR while the proceeds were used for services including staff welfare, maintenance of facilities and beautification of the university premises. A further analysis of data showed that there was a significant relationship between internally generated resources and the management and development of universities in Southern Nigeria. It is recommended that university administrators should be more transformative in their leadership style in order to strengthen their revenue base for effectiveness in University management.</p>

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 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)0.001
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 score0.069
Threshold uncertainty score0.104

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.013
GPT teacher head0.317
Teacher spread0.304 · 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