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Record W2930548452 · doi:10.5539/ijel.v9n3p126

Dialogical Dynamics and Subversions of Political and Ideological Boundaries in Chinua Achebe’s Anthills of the Savannah

2019· article· en· W2930548452 on OpenAlexvenueno aff
Motasim Almwajeh

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLiterary Theory and Cultural Hermeneutics
Canadian institutionsnot available
Fundersnot available
KeywordsDialogical selfIdeologyEcofeminismPoliticsSociologyOppressionRealmGender studiesAestheticsEnvironmental ethicsEpistemologyLawPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

This article examines the subtle allegorical political nuances and implications in Chinua Achebe’s Anthills of the Savannah (1987). The novel foregrounds and grapples with the problematics of voice, representation, and history where the more inclusive voice appears to be, the more suppressive and exclusive of other voices it is. Hence, the text enacts a journey toward a realm that rises above gender and class-based rigidities, fusing facets of Nigerian sociopolitical and environmental crises (in the past and present). The novel takes on multiple narratives that engender continuation and sharing vis-à-vis historical realities of political cleansing and ideologies and systems of exclusion. Counteracting condescendingly patronizing doctrines and reductive dichotomies, dialogism and ecofeminism pay equal attention to all parties and reject polarizations and divisions. A combination of these approaches precludes tantalization, and it also humanizes ecofeminism and gives it a wider scope. In principle, combined, these approaches guard against any rejectionist or exclusionary superstructures they seek to deconstruct. Ecofeminism, much like Bakhtinian dialogism in its quest for justice, hinges environmental degradation to gender-based, class-based, racist, and imperial variables, and it disrupts these ideologies and systems of oppression in order to assuage human and nonhuman conditions.

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)0.000
metaresearch head score (Gemma)0.007
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 score0.453
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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
Published2019
Admission routes1
Has abstractyes

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