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Record W2910418546 · doi:10.5539/ijef.v11n2p137

The Impact of the Intellectual Capital of the University Administration in Achieving the Quality of Education

2019· article· en· W2910418546 on OpenAlexvenueno aff
Saqer Al-Tahat, Alaa Jaber Matarneh, Osama Abdul Moneim Ali

Bibliographic record

VenueInternational Journal of Economics and Finance · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual capitalPossession (linguistics)Quality (philosophy)Administration (probate law)Order (exchange)Relational capitalSample (material)PopulationCapital (architecture)Resource (disambiguation)BusinessManagementPolitical sciencePublic relationsSociologyEconomicsFinanceLawComputer science

Abstract

fetched live from OpenAlex

The rational and entrepreneurial universities are working in the possession of an important resource, which is the intellectual capital, to reach the local and  global leadership, Such study aims at stating the intellectual capital impact of the rational university administration in accomplishing its quality of education since the study population consisted of both public and private Jordanian University while the study sample reached to (45) faculty members were chosen randomly and were working in such Universities, a questionnaire has been designed and distributed on (45) faculty members of the study population, who were working in such Universities, for the purpose of achieving the study aims as well as the essential statistical exams have been conducted whereas the findings showed that there is an impact of the intellectual capital) for the rational University administration of the different kinds of the Universities (the humankind, the structural, and the relational in achieving its quality of education while the study recommendations revolve around the necessity of the Universities in identifying the intellectual capital and determining the practical means to preserve and improve it in order to guarantee its quality of education.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.090

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)0.0000.000

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 head0.239
Teacher spread0.226 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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