Refiguring Italian Cultural Quarters: "Il Ghetto di Venezia. 500 anni di vita" [The Venice Ghetto. 500 Years of Life] (Film by Emanuela Giordano, 2015) and "Primavere e Autunni" [Springs and Autumns] (Graphic Novel by Ciaj Rocchi and Matteo Demonte, 2015)
Bibliographic record
Abstract
This piece briefly summarizes the contents of part of a University course in cultural geography held at the University of Padua in the 2015/16 academic year, with the aim of suggesting a possible didactical contextualization for two recent creative works devoted to very different examples of “cultural quarters” in Italy (the Venetian Jewish quarter and so-called “Milan’s Chinatown”). The very first notion of comparing the docufilm Il Ghetto di Venezia. 500 anni di vita [The Venice Ghetto. 500 Years of Life] (2015) and the graphic novel Primavere e Autunni [Springs and Autumns] (2015) originated from a purely formal appreciation of them. The works, in fact, both present pieces of creative cartography of the cultural quarter, which have particularly stimulated our imaginations as cultural geographers (Figs 1 and 2). Subsequently, a deeper analysis of the complex implications of these informed and carefully arranged creative works led us to consider them precious resources for the teaching of cultural geography. Creative works became crucial given that we built upon them educational projects that refer to complex, transcalar, and multidimensional relations between cultural processes and spaces. In the initial part of this article, therefore, we draw on recent international and Italian literature on ethnic spatial concentration to contextualize the two works presented here.
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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 | 0.004 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".