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Record W4407886573 · doi:10.38159/jelt.2025624

Let Peace Reign: Introducing Peace Education for Nigerian National Transformation

2025· article· en· W4407886573 on OpenAlexaff
Kelechi Johnmary Ani

Bibliographic record

VenueJournal of Education and Learning Technology · 2025
Typearticle
Languageen
FieldComputer Science
TopicEducational Challenges and Innovations
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsReignTransformation (genetics)Peace educationPolitical scienceAncient historyPublic administrationHistoryLawChemistryPolitics

Abstract

fetched live from OpenAlex

The increasing quest for peace in the globe is directly connected to the place of conflict, disaster and crisis in undermining the peace and good life of the masses. The impact of conflict in undermining national peace in the Nigerian state has remained problematic. This study thus focuses on the place of peace education in the quest for Nigerian national transformation. It used secondary data from literature to analyze the nature of peace education. Consequently, the study separated the nature of formal and informal peace education as well as the necessary topics that would be taught both in the formal and informal learning settings. It recommends the multiple paths to the transformation of the Nigerian peace research institutes as a way of promoting national peace, security and development. This study will contribute to the body of knowledge in the area of peace education and peacebuilding in Nigeria. Keywords: Peace Education, Conflict, Peace Research, National Transformation, Nigeria

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0040.005
Open science0.0000.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.321
Teacher spread0.307 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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