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Record W2621689960 · doi:10.5539/mas.v11n7p57

Federalism as Protagonist or as Nemesis for Nigeria’S Political Development

2017· article· en· W2621689960 on OpenAlexvenueaboutno aff
Babatunde Oyedeji

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsFederalismPoliticsDual federalismPolitical economyPolitical scienceAutocracyPopulationTypologyPolitical instabilityFeelingDemocracyDevelopment economicsSociologyLawEconomicsDemography

Abstract

fetched live from OpenAlex

Despite the plethora of findings and feelings surrounding federalism and the acerbity of the cynical discomfort at the negative nuances about the ideology, the federal system has produced stable and settled societies in Canada, Australia, the United States of America, India, Germany, Switzerland, New Zealand, Brazil, Malaysia and Mexico. Nevertheless, the frequent conclusion is its inherent attraction to ‘inevitability of instability’ generally in Africa and specifically in Nigeria. This typology seems to apply to developing countries more than others, in any case, at least nineteen countries containing some 40% of the world’s population. This puts and acute pressure on Nigeria, the surviving big federal country in Africa. It can be asked, did the British leave meaningful alternatives to federalism whilst ruling Nigeria between 1900 and 1914 and 1960? Can’t it not be deduced that federalism was indeed a natural product of decisions and phenomena like the Indirect Rule, the political activism on the part of Southern Nigerian politicians. Was the complex nature of Nigeria’s federalism a product of residual colonialist autocracy? The paper aims at delving into variants contributing to the sticky challenge and complexities of the Nigerian federation. It would be expository and analytical as it examines the advantages and attractions prior to the shortcomings and deficiencies of federalism. There would be references to the applicability of these deductions to the Nigerian example.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.011
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.379
Teacher spread0.324 · 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 designTheoretical or conceptual
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

Citations1
Published2017
Admission routes2
Has abstractyes

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