Eclipse in Rwanda as Remembering in Pyschosocial Poetics of Trauma
Bibliographic record
Abstract
Trauma exists in a synthetic mode of the referential and this is the underlying temperament in Eclipse in Rwanda. The genocide that is chronicled in the narratives of the Nigerian Civil war as recreated in Joe Ushie’s Eclipse in Rwanda foreshadows the pogrom in the mid 90s. Using Cathy Caruth’s concept of trauma as a theoretical framework, this paper examines Eclipse in Rwanda as remembering in psychosocial poetics of trauma. This paper further explicates Eclipse in Rwanda as a text of memory, which poetically captures the trauma and foreshadows the social construction of natives/ non-natives in Africa at large and in Nigeria in particular. Through the poems analysed in this paper, our findings show that Tutsis’ genocide is a poetic fulcrum for the poet to pensively recall the Nigerian Civil War and other hotspots/ narratives of politically motivated violence against fellow citizens. Eclipse in Rwanda attempts to entrench the memories of the dead in us through the poetics of remembering and by so doing indict the collective consciences of the society.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".