<i>La passeggiata prima di cena</i>: percorsi dello sguardo, e la lezione di Georges Seurat
Bibliographic record
Abstract
L’articolo offre un’analisi dei legami intertestuali esistenti tra il racconto “La passeggiata prima di cena” di Giorgio Bassani ed il dipinto Un dimanche après-midi à l’Île de la Grande Jatte di Georges Seurat. In particolare, l’articolo illustra questa relazione alla luce del dibattito italiano sul post-impressionismo mettendo in evidenza come, nel solco di questo discorso critico, Bassani cerchi di integrare nel proprio racconto una serie di strategie visive, formali e poetiche riconducibili al dipinto di Seurat. Infine, attraverso una lettura al tempo stesso semiotica e psicanalitica del rapporto fra testo scritto e intertesto visivo, l’articolo si propone di ricondurre le modalità di questa relazione alla costruzione in Bassani di un’identità narrativa volta a rappresentare un primo passo nella costruzione dell’autore implicito di il romanzo di Ferrara.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.016 |
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; both teacher heads agree on what is shown here.
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".