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Legal Regime for Exploring Solid Minerals for Economic Growth in Nigeria

2013· article· en· W1559916794 on OpenAlexvenueno aff
Adeniyi . I. Olatunbosun, Michael .O. Adeleke, Olabode .O. Ayorinde

Bibliographic record

VenueCanadian social science · 2013
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityBusinessProduct (mathematics)Natural resourceGross domestic productResource (disambiguation)Benchmark (surveying)Sustainable developmentNatural resource economicsEconomic growthEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Solid minerals as natural resource help to grow the economy, create jobs, and generate enduring wealth for the people of Nigeria. Effective mining will transform the Nigerian economy and create a suitable and enabling environment for productive activities to flourish. It is imperative to adopt international best practices as the national benchmark to evaluate the standards of the mining operations and provide accessible financing scheme for local investors and conducive atmosphere to attract foreign investors’ participation. However, from the mining sector to thrive and contribute significantly to the gross domestic product, the sector requires the enactment of potent legal instruments and the establishment of virile institutional agencies with a view to regulating the exploration of mining activities and controlling the persistent high level of insecurity, revamping on the worsening power supply for optimum productivity in achieving sustainable development.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.996

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 head0.032
GPT teacher head0.238
Teacher spread0.206 · 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 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

Citations6
Published2013
Admission routes1
Has abstractyes

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