Per una grammatica dello spazio. Montreal, L’Aquila, Venezia: tre citta in traduzione
Bibliographic record
Abstract
The concept of “cities in translation”, derived from the work of Canadian researcher Sherry Simon (2008; 2013), opens the way to a perception of languages as active forces in the transformation of the cities we inhabit. If Simon focuses on bilingual cities, and in particular on Montréal, analysing the continuous transitions from one language to another, it would be even more interesting to analyse the space between languages, moving in the direction of a study of the heterolinguism inherent in each space, that is, the intrinsic plurality of each space and of its voices. This article will place the case of Montreal alongside that of two Italian cities, L’Aquila and Venice, in an attempt to broaden the concept of the translational or “post-translational” city, thanks to the reading of the different but complementary ways of living in translation that these cities show us, in a physical and metaphorical sense. These pages cannot, of course, fulfil the task of outlining a real method of analysis of the city in translation, but rather aspire to open up a field, that of translation studies, to a true and profound encounter with the reality of contemporary urban spaces. The intention is therefore to contribute to a “linguistique d’intervention” that can act where languages are used and where languages influence our ways of living, that is, on what Gaffuri (2019) calls the “imaginaires de la vi(ll)e”, because space is not alone but is “consubstantial” to the languages that inhabit it and contribute to its formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 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".