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Record W2159058505 · doi:10.5539/ijms.v5n1p128

Political Marketing: An Effective Strategy for Quality Leadership and Sustainable Democracy in Nigeria

2013· article· en· W2159058505 on OpenAlexvenueno aff
Olafemi Ayopo Olotu, Victor Olukayode Ogunro

Bibliographic record

VenueInternational Journal of Marketing Studies · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyPoliticsSafeguardingDemocratizationQuality (philosophy)Political scienceCorporate governancePublic relationsSociologyPublic administrationEconomicsManagementLaw

Abstract

fetched live from OpenAlex

Democracy stands for the rule of law, mutual consultation in matters of governance and the safeguarding of human rights brought about through quality leadership. This philosophical view forms the political hallmark of any nation including Nigeria. Unfortunately, democratization in Nigeria has remained nascent and quality leadership a mirage. This was largely due to the mis-conception given to the exchange theory concept in the Politician-Electorate relationships. The study identified Apolitical Marketing as the bane of sustainable democracy in Nigeria, thus the non-application of the concept of “customer first” (Electorate) is responsible for poor leadership. The author revealed that Political Marketing Research, Internal Democracy, Relational Politics and Green Politics are holistic in the drive toward good leadership and democratic sustainability. It was thus, recommended that Nigeria political class, umpires and leaders should invest very high proportion of their resources on research and intelligence gathering on the voters and embraces the holistic marketing concept geared toward a lasting, enduring and beneficial democracy.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.055
GPT teacher head0.333
Teacher spread0.278 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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