M. NourbeSe Philip’s Poetics of Justice: Reacquiring the Tongue, (W)ri(gh)ting African-Caribbean History
Bibliographic record
Abstract
Trinidadian Canadian poet M. NourbeSe Philip practised Law for seven years in Toronto before devoting her life to her writing in 1983. Philip’s work is a hybrid mixture of genres as over the last decades the author produced a number of prolific essays, fiction and poetry work. To her, law and poetry share an obsession with language and in fact, her work is influenced by the material and concrete aspect of the legal text as well as by the fluid and abstract nature of the poetic text. Philip’s work is reminiscent of a poetic court where the writer appears to take proceedings against dominant discourses or to turn the previously accepted evidence upside down while the reader becomes a juror who is to return a new verdict. As ’she tries her tongue’ (1989), Philip aims at retelling African Caribbean history from the perspective of the oppressed thus demonstrating how fundamental it is for the Caribbean writer to engage with history. As a matter of fact, this paper seeks to demonstrate to what extent Philip’s former profession has contributed to shape her writing through which she attempts to reacquire her tongue and to express her thirst for historical truth and social justice. Hence, to what degree are legal and Euro-centric accounts of African history being challenged by Philip’s texts? Ultimately, does the fragmentation of the text genuinely allow the poet to write/right her history, to mourn her African ancestors and to ’make the black hole (w) hole’ (1997)?
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".