Bibliographic record
Abstract
Marxist theory or Marxist criticism, one of the theories used in literary criticism, is based on the ideologies of Karl Marx and Friedrich Engels who argue that all societies (with the exception of primitive hunter/gatherers) are divided along class lines and are characterised by class struggle. This paper examines Sam Aihimegbe’s Blood in the Creek as a reflection of Marx’s explanation regarding the class struggle between the bourgeoisie and proletariat resulting from economic, political and social imbalances. Marxism here is used as a lens to unveil how the capitalists: Government, their friends and oil companies explore the oil resources of Odi and other parts of the Niger Delta only for their financial benefits without consideration of the proletariat, the working class. In the face of uneven distribution of resources among the strata of the society, the masses revolt and this revolution is met with stiff resistance from the oil benefactors. This paper argues that studying Blood in the Creek from a Marxist perspective assists to reveal layers of crisis between the capitalist and the working class. It uses literature to x-ray oil issues raised in the narrative, and seeks to proffer solution to the crisis between the bourgeoisie and proletariat.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".