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Record W1516736199 · doi:10.7176/nmmc.vol189-14

Jos Crisis and the Challenge of Managing Cultural Differences

2013· article· en· W1516736199 on OpenAlexaboutno aff
Fred A. Amadi

Bibliographic record

VenueJournals & Books Hosting (International Knowledge Sharing Platform) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperNigeriansMulticulturalismGovernment (linguistics)Character (mathematics)SociologyPolitical scienceSocial scienceLawMedia studiesLinguistics

Abstract

fetched live from OpenAlex

This paper is an analysis of how the Nigerian government manages cultural differences, especially the type that is causing the crisis in Jos, Nigeria.I sampled textual exemplars from Nigerian newspapers.The newspaper texts served as part of the data used for the analysis.The sampled texts are displayed on a titled text box and interpreted.Comments given by two interviewees representing opposing sides in the Jos crisis are also displayed.Methods of Critical Discourse Analysis are used to interpret and discuss the newspaper texts and the comments given by the interviewees.The discussion reveals that flaws in the implementation of multicultural policy are the cause of the recurrent crisis in Jos. Discussion on multiculturalism found flaws in how Canada and other Western countries handle liberal multiculturalism.Discussion also reveals that even when a new policy is devised to solve the Jos crisis, the Nigerian government would be reluctant to accept the policy if the acceptance gets suspected of having a potential to undermine its Federal Character policy.The paper also found that government's reluctance has not deterred other Nigerians from pushing for possible innovative ways of managing the ever-increasing cultural problems besetting 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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.123
GPT teacher head0.381
Teacher spread0.258 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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