Bibliographic record
Abstract
In this essay, I analyze Joan Anim-Addo’s libretto Imoinda, or She Who Will Lose Her Name (2008) and illustrate how its narrative poetry generates a speculative, gendered history around the slave past. Informed by Srinivas Aravamudan’s observation of parodic subversion in the afterlives of Aphra Behn’s Oroonoko (1688), I return to Anim-Addo’s oeuvre in order to read Imoinda as a work that counter-writes the colonial gaze of “Western” knowledge. By centering on Caribbean carnival as the performance context for the libretto, I examine how histories of rebellion and survival carried out by enslaved Africans and their descendants unfold through the libretto’s narrative poetry. I argue that Imoinda, under the guise of artistic forms associated with “the West,” breaks from Eurocentric perspectives that misrepresented subaltern struggles while ushering forth the question of “who speaks?” in critical discourses. I conclude by aligning Anim-Addo’s Imoinda in relation to Sylvia Wynter’s conceptualization of “demonic grounds” to highlight a transformative epistemic space of Caribbean women’s literature.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".