Lo specchio dell’io ritornando da scrittrici
Bibliographic record
Abstract
Nella prima raccolta di poesie, Flower of Youth, Mary di Michele si trova a Casarsa delle Delizie dove viaggia attraverso il passato giovanile e problematico di Pier Paolo Pasolini, rispecchiandosi nella sua ricerca di creatività, passione, comprensione, perdono. In Solitaria, Genni Gunn viaggia in Puglia, alla ricerca dei luoghi, miti, superstizioni e credenze degli antenati di sua madre: attraverso il personaggio di Davide, ragazzo italo-canadese e suo alter ego la scrittrice dà voce ad una duplice cultura, doppia lingua e capacità meta-creativa. Entrambe le opere presentano il viaggio di ritorno in Italia come trasformazione e specchio delle proprie capacità creative.A Mirror for the Self. Getting back as a WriterIn her first collection of poems, Flower of Youth, we find Mary di Michele in Casarsa della Delizia moving through Pier Paolo Pasolini’s troublesome youth, projecting herself in his own creativity, passions, sympathy, forgiveness. In Solitaria, Genni Gunn, instead, travels to Puglia, searching for places, myths, superstitions, beliefs of her mother’s ancestry. Tha main character, the alter ego of the writer, is Davide, an Italian Canadian young boy who represents the ambiguity of a double culture, a double language and meta-creative skills. Both these works focus on getting back to Italy as an experience of transformation and projection of their creative ability.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".