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Oral Poetry as Channel for Communication

2012· article· en· W2130431178 on OpenAlexvenueno aff
Obaje A. Anthony, Yakubu Bola Olajide

Bibliographic record

VenueCross-cultural communication · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPraisePoetryBantu languagesOral poetryCultural heritageAtmosphere (unit)PoliticsOral literatureAestheticsSociologyHistoryLiteratureArtGeographyLinguisticsPolitical scienceLawPhilosophyArchaeology

Abstract

fetched live from OpenAlex

African village traditionally was a small unit where every inhabitant knew and was interested in the affair of his neighbor. This common heritage produces poems passed on by words of mouth from one generation to another. This paper discusses the transmission of African socio-cultural values from one generation to another through oral poetry. It explains its common heritage and modus operandi, which creates the desired atmosphere and evokes the appropriate emotions as demanded by the occasion. The paper also literarily exemplifies the significance of the communication between the living and the dead, the listeners (audience) and the mistrels, praise singers, and the traveling bards of the Ewe of Ghana, the Bantu of South Africa, the Yorubas and Hausas of Nigeria, the Berber of Algeria and the Gikuyu of Kenya. The modes of political poetry in every one of these oral groups and their quest for cultural rehabilitation are encapsulated in the discourse.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.011
Scholarly communication0.0120.009
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.003

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 head0.066
GPT teacher head0.340
Teacher spread0.274 · 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 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
Published2012
Admission routes1
Has abstractyes

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