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Record W1582656570 · doi:10.3968/6900

Religious Ethics and Development: The Nigerian Experience

2015· article· en· W1582656570 on OpenAlexvenueno aff
S. Awoniyi

Bibliographic record

VenueStudies in sociology of science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsNigeriansPeasantPovertyIslamCycle of povertyIdeologySociologyCorrupt practicesConfusionInsurgencyProductivityDemocracyCapital (architecture)Development economicsPolitical sciencePolitical economyEconomic growthLawPoliticsEconomicsPsychologyHistory

Abstract

fetched live from OpenAlex

Nigerians, like most fellow Africans, are still living in confusion greatly influenced by the Boko Haram insurgency and bankruptcy of imported Islamic ideologies. In actual fact today, Nigerians real capital comprises the peasant masses, thousands of jobless youths and graduates, the homeless, the armed robbers, the sick and the destitute who struggle daily for survival. Thus, the majority of the people have remained permanently marginalized by the current vicious cycle of poverty and dependence. Unfortunately however, successive Nigerian leaders have been using religion as an instrument of playing divide-and-rule game, rather than as a springboard for the inculcation and improvement of social ethical values which are fundamental to achieving correct human behaviour as it relates to productivity and nation-building. This paper therefore examines the place of religion in the development of Nigeria with a view to generating new ideas that will contribute meaningfully to the search for democratic principles and ideals that would usher in a well-ordered society, not only in Nigeria, but in Africa as a whole.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.116
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 head0.332
GPT teacher head0.517
Teacher spread0.186 · 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.

Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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