Bibliographic record
Abstract
There is no doubt that one of the unresolved contradictions of representation in postcolonial fiction is that of the relation between the colonizer and the colonized. This issue generates a wide spectrum of critical hues, exploring how present circumstances shape a postcolonial narrative technique. The present paper explores Ben Okri’s In Arcadia (2002), attempts to display this innovative disturbing representation by investigating the narrative experimentation in the novel of Ben Okri. Okri’s novel reflects the dilemma of individual freedom and libration, and the contemporary situation of fragmentation, rootlessness, dehumanization, displacement, and disorientation in a world where man finds himself suspended in a void of meanings. Okri’s response to this dilemma is given by those scapes which become the new responsible creators of their own world by shaping fresh values, lives, and realities, which is reflected in the reshaping of the narrative mode of a postcolonial and postmodern Nigerian novelist, tempered with the narrative form and its representation of the experience of reality. His fiction has subverted the narrative modes of representation thereby dislocating the structure of narrative technique through the juxtaposition of spatial fragments from different situations. Thus, the hypothesis was that it would be valuable to analyze and examine Okri’s narrative experimentation as a contemporary writer, in order to see the extent of innovative progression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".