A Comparative Study of Postcolonial Aspects in T. Salih’s Season of Migration to the North and C. Achebe’s No Longer at Ease
Bibliographic record
Abstract
This study aims at investigating aspects of coloniality in both novels of the title. The two works expose a number of the evils of coloniality like masked colonisation, stereotyping and hybridity. The coloniser’s appointing of national agents to run the country in the coloniser’s stead, raising nonentities on the political hierarchy and sowing seeds of hatred among citizens of the same nation will be discussed under the first subtitle, masked colonisation. Under the second, stereotyping and misrepresenting Africans will be investigated. The paper will discuss ideas of language, culture and religion when dealing with hybridity, the third concept in such a trichotomy, to show how these have been affected by colonisation. The paper will respond to the following questions: how do Achebe’s No Longer at Ease and Salih’s Season of Migration to the North question the credibility of achieving independence? How (and why) did the (British) coloniser persistently stereotype African nations? How did the evil aftermaths of British colonialism reach and spoil the different aspects of the lives of the colonised nations, as shown in both?
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".