Bibliographic record
Abstract
Abstract: HMS Nimble , a Royal Navy schooner having recently captured a Spanish slaver and taken aboard 272 slaves, ran ashore at nighttime in bad weather on the Cuban coast in November 1834. While all crew were saved, several dozen of the African recaptives aboard lost their lives in the accident, which according to the Nimble ’s master had occurred because the “uncontrollable noise of these savages” had made it impossible to hear the breaking of the waves on the reef. What emerges from a detailed reconstruction of the perceptions of the accident as evident in the court martial documents is a specific imaginary of the comical, based on a profound lack of mastery over the moving parts of the situation—natural, technical, and social. This imaginary is intimately related to the moral language of humanitarianism but also adds to the patterns of victimization and the cruel ironies of abolition. Abstract: Le HMS Nimble , une goélette de la Marine royale qui venait de saisir un navire de traite espagnol et de prendre à son bord 272 esclaves, s’est échoué de nuit par mauvais temps sur la côte cubaine en novembre 1834. Si tous les membres de l’équipage ont pu être sauvés, plusieurs dizaines d’esclaves africains qui se trouvaient à bord ont perdu la vie dans cet accident qui, selon le capitaine du Nimble , s’est produit parce que le « bruit incontrôlable de ces sauvages » avait empêché d’entendre le déferlement des vagues sur les récifs. Ce qui se dégage d’une reconstruction détaillée des perceptions de l’accident telles qu’elles ressortent des documents de la cour martiale, c’est un imaginaire spécifique du comique, fondé sur un profond manque de maîtrise des éléments mobiles de la situation — naturels, techniques et sociaux. Cet imaginaire est intimement lié au langage moral de l’humanitarisme, mais il s’ajoute également aux modèles de victimisation et aux ironies cruelles de l’abolition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".