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Record W1966501829 · doi:10.1504/ijimb.2015.068154

A conceptual analysis of halal beef value chain and market potential in Nigeria

2015· article· en· W1966501829 on OpenAlexaboutno aff
Musa Gambo Kasuwar Kuka, Balarabe A. Jakada

Bibliographic record

VenueInternational Journal of Islamic Marketing and Branding · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHalal products and consumer behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationBusinessValue (mathematics)State (computer science)GeographyEconomyEconomics

Abstract

fetched live from OpenAlex

It has been observed that many literatures on halal products and Muslim population in Africa tend to concentrate on North African countries such as Algeria, Egypt, Libya, Morocco, Tunisia or that of South Africa which has less than 2 million Muslims. But Nigeria with more than 50 million Muslim population is ignored surprisingly. This paper attempts to address this seeming anomaly by providing factual insights into the market potential of halal beef in Nigeria. It reviews relevant literatures on halal products, Muslim population and demand through in–depth conceptual analysis on the materials obtained. The analysis shows that Nigeria promises to be a lucrative halal market in Africa due to its population. Its market potential is by far more than South Africa and Saudi Arabia put together. In fact, with a population of over 9 million, Kano State of Nigeria has a halal market potential higher than that of South Africa, Germany, UK, Italy, Brazil and Canada put together. As such Nigeria can be regarded as halal market goldmine that is lying untapped. What is needed is for halal beef processing companies to come and explore the halal market goldmine.

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)0.005
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 score0.062
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 head0.019
GPT teacher head0.304
Teacher spread0.285 · 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
Published2015
Admission routes1
Has abstractyes

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