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Record W4388235240 · doi:10.25159/2663-6565/12532

Niger Delta Subaltern Agency and Resistance in Obari Gomba’s The Ascent Stone and Stephen Kekeghe’s Rumbling Sky

2023· article· en· W4388235240 on OpenAlexaff
Mathias Iroro Orhero

Bibliographic record

VenueImbizo · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSubalternInsurgencySociologyAgency (philosophy)Resistance (ecology)Power (physics)Gender studiesPoliticsAestheticsLawPolitical scienceSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

This article applies the theoretical positions of some scholars from the Subaltern Studies Collective to the reading of poetry by Niger Delta writers. I argue that the Niger Delta people are subaltern in the Nigerian national space due to their disadvantaged sociopolitical position as well as the resource conflict that has left the region at the mercy of the state and its agents. With insights from the writings of Ranajit Guha, Dipesh Chakrabarty, Gyan Prakash, Gayatri Chakravorty Spivak, and Partha Chatterjee, I read the subaltern themes of agency and resistance in Obari Gomba’s The Ascent Stone and Stephen Kekeghe’s Rumbling Sky. In adopting this framework, I draw from Guha’s original theorisation of peasant insurgency and the structure of power as well as later theorisations of relational power discourse and subaltern agency. My close reading of selected poems reveals the figure of the Niger Delta subaltern as the architect of their own destiny and whose resistance haunts the dominant discourse of the nation. The notions of insurgency, the nation and its fragments, failed revolutions, and relational power discourse are deployed as hermeneutical strategies. My adoption of this theoretical approach recovers its insights for the reading of literary works by writers from minority groups.

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)0.002
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.012
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0010.002
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 head0.034
GPT teacher head0.248
Teacher spread0.214 · 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
Published2023
Admission routes1
Has abstractyes

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