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Record W2965828041 · doi:10.3968/11052

Igbo Numerical System and Mathematics: Towards Harnessing Potential for Business, Governance, Science and Technology

2019· article· en· W2965828041 on OpenAlexvenueno aff
BonaChristus Umeogu, Chukwuemeka Nelson Etodike, Ifeanyichukwu Jude Onebunne, Ifeoma C. Ojiakor

Bibliographic record

VenueCanadian social science · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Linguistics, Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIgboCorporate governanceMeaning (existential)IndigenousSociologyMathematicsComputer scienceSocial scienceBusinessEpistemologyManagementEconomicsPhilosophy

Abstract

fetched live from OpenAlex

This study explored the nature of Igbo numerical system and mathematics towards harnessing its potential for business, governance and science and technology. Like other civilizations, Igbo mathematics evolved from its numerical system which is aboriginally vegesimal number system (of base 20). The Igbo number system was advanced because it has number names for all the numbers within its vegesimal system although the numerals were not symbolized. Outside its general and conventional use, the Igbo numbers do have social and religious implied meaning which influenced the use of the numbers and the people. The cultural influence of this number system to a large extent determined the utility and application of same in mathematical principles and later in its outcome as human development. Some humanistic aspects were implicated such as business enterprise, governance and science and technology as areas where the application potentials of indigenous numerical system and mathematical expressions in daily usage and science can be harnessed for greater benefits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.026
Scholarly communication0.0080.006
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.214
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2019
Admission routes1
Has abstractyes

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