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Record W1859798079

The Military as a Motif in the Nigerian Novel: Helon Habila’S Waiting for an Angel

2011· article· en· W1859798079 on OpenAlexvenueno aff
Jonas Egbudu Akung, Ed Simon

Bibliographic record

VenueStudies in literature and language · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyMotif (music)LawLanguage changeSociologyPolitical scienceAestheticsLiteraturePoliticsPhilosophyArt
DOInot available

Abstract

fetched live from OpenAlex

Abstract This paper examines the continuous presence of the military as a motif in the Nigerian novel. It examines the paradigm shift from the older generation of Nigerian novelists who saw the military as corrective mechanism to the younger generation of Nigerian novelist who hold that the military is the bane of the decay that has come to envelop the modern Nigerian society. It is the position of this paper that ideologically, the military cannot be seen as a corrective mechanism. This is because it is responsible for the corruption religious malaise, academic rot and human right abuses among other observations that have bedeviled the Nigerian society. These among others are the issues which this paper has set out to discuss. Finally, the paper concludes the civil rule should left for civil authority while the military should remain within its orbit of protecting the territorial integrity off the nation. Key words : Scaffolding; Zone of Proximal Development; Peer review

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)0.003
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.013
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.300
Teacher spread0.228 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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