How the concept of world literature calls its own crime fiction sub-genres to life : a Cuban case study
Bibliographic record
Abstract
Goethe, the founding father of Weltliteratur as we know it today, first started lobbying for a unified world literature to counteract the destabilizing fragmentation underlying most of the late eighteenth and early nineteenth century; a fragmentation to which we can relate today and which, probably, best explains our renewed interest in the concept of world literature. Weltliteratur was to be a vehicle for the worldwide spread of humanist ideals and values and Goethe's language of choice, which would act as a sort of arbiter for the dissemination of work in foreign languages throughout Europe, was his own native German. Fast-forwarding a century or two, the Eurocentric undertones of Goethe's well-intended enterprise have barely changed or shifted. The main difference is that with the U.S.A. as the world's only superpower it is English and not German that has become the lingua franca of world literature. In this paper, I discuss a case study on two ethnic detective novels set in Cuba where one originates from a cultural outsider, i.e., The Beggar's Opera (2012) by Canadian Peggy Blair, and the other is written from an insider's perspective, i.e., Pasado perfecto (2001) by Cuban Leonardo Padura, in order to argue that the above-mentioned essentializing "Anglophony" is inextricably intertwined with the current understanding of world literature. The consequence hereof is a perpetuation of the old notions of centers and margins that the new comparative literature model is supposedly countering.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.029 | 0.012 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| 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".