Canisia Lubrin. <i>Code Noir</i>: Metamorphosis. Toronto: Knopf Canada, 2024, 346 pp.
Bibliographic record
Abstract
What are we doing here, where every other sentence hides the one that came before it, so that language becomes the material of this account?"Canisia Lubrin writes this in her poetic collection of fifty-nine fiction pieces paired with the fifty-nine artistic depictions and reproduction of the articles of Code Noir by artist Torkwase Dyson.Code Noir is a set of historical decrees that were passed in 1685 by King Louis XIV of France that define the conditions of slavery in the French colonial empire.I have thought about how we decolonize the law that I teach in an institution that boasts a bilingual, bijuridical education in both the common-law and civil-law traditions.How do we teach, knowing that the law in place is colonial, and how do we understand law, knowing its oppressive, violent, and racist foundations?Lubrin's book provides a breathtaking and invigorating way into the legal, contemporary discussion of how Code Noir still contributes to the imprisonment, deportation, and dehumanization of Black persons in the former French colonies.While not doctrinal, the book carries long-held traditions of narrative as method paired with the stark visual art of the code with black shading.In the art, each of the articles of Code Noir are subject to a redacting effect and, in my experience as a lawyer, seeing the black stripes in documents can be a frustrating and infuriating experience.The art provides a dual experience.At once, it is a dissatisfying disclosure that is not only aimed at shielding or covering up nefarious government action from transparent oversight, but also performs as a grotesque artefact, claiming that it is only part of the past.On the other hand, the text, readable through the smudging, makes known the common aspects that show up in law today.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.465 | 0.236 |
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".