Bibliographic record
Abstract
This article addresses Magris’s appropriation of classical myth in his postmillennial narrative. Since his early works of literary criticism Magris explored the world of myth and the mythopoeic power of literature, but only in his postmillennial texts has he undertaken the writing of what John J. White defines as “mythological” narratives, in which he engages with the reuse and not the creation of myths. This article focuses on three works: La mostra (2001), Alla cieca (2005), and Lei dunque capirà (2006). It evaluates them as a cycle of closely connected mythological texts, built upon the intertextualization of: the myth of Alcestis, the myth of Jason and the Argonauts, and the myth of Orpheus and Eurydice. Magris’s postmodern investigation of individual and collective histories unveils their traumatic relationship to memory and the impossibility of their unequivocal and coherent representation. The monologue Lei dunque capirà is Magris’s most focused and comprehensive reworking of a classical myth in which a modern Eurydice retells from her standpoint the story of Orpheus’ descent to the underworld. The text is an investigation of myth from a feminist perspective and at the same time an exploration of the theme of love voiced with the mixture of judgment and understanding that only conjugal love allows.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".