Frame Narrative Technique: Paralleled Heterotopias in Mohamed Rageh's A Quarter Citizen
Bibliographic record
Abstract
The research has a threefold literary approach with a psychological, philosophical as well as a technical perspective. It aims at examining the narrative technique used by Egyptian novelist and script writer Mohamed Rageh in A Quarter Citizen. The research seeks to show Rageh’s novel as belonging to the narrative therapy type. It suggests that following this type of therapeutic narrative, Rageh builds heavily on the Michael Foucault’s concept of ‘heterotopia’ and frame narrative technique. This could be traced in the novel’s presentation of different types of heterotopias together with a form of frame narrative exemplified in his presentation of a script- within- a novel technique. This sets narration in Rageh’s A Quarter Citizen as starkly built on parallelism and juxtaposition. In his scenanovel, as he ventures to calls it, Rageh juxtaposes the protagonist's true experience with a different version of it rendered in the form of a script. A further type of parallel in the novel is that between different forms of 'heterotopias' especially the prison as heterotopias of deviation where the larger part of the novel's actions take place. In light of this, the research seeks to trace the extent to which narration was an aid to the novel's protagonist and how far it helped him to relieve his psychic disturbances resulted from his incarceration experience. In so doing, the research poses the question whether narration in Rageh's A Quarter Citizen proves to be therapeutic or not and if it successfully follows the two prerequisite steps of narrative therapy namely externalization and suggestion. Further questions are concerned with the therapeutic role played by the script/ heterotopia and the models of identity building suggested by the script.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".