Iuav Academics Abroad : una "citta analoga" per Venezia = an "analogous city" for Venice
Bibliographic record
Abstract
Questo volume presenta gli atti della reunion “Iuav Academics Abroad. Strategie di internazionalizzazione” tenutasi in Aula Tafuri a Palazzo Badoer il 22 marzo 2019 in seno agli eventi dedicati al network “Iuav Abroad” della Università Iuav di Venezia in collaborazione con Iuav Alumni \nLe attività promosse sono a cura di Alberto Ferlenga, Benno Albrecht, Enrico Fontanari, Emanuela Sorbo, Elisa Brusegan \nHanno partecipato Gustavo Adolfo Carabajal, Universidad Nacional de Rosario, Rosario (Argentina); Serena Conti, Université Libre de Bruxelles, Bruxelles (Belgio); Maroun Daccache, Lebanese American University, Byblos (Libano); Luca Donner, Canadian University Dubai, Dubai (EAU); Azad Hama, Tishk International University, Erbil (Iraq); Carla Keyvanian Auburn University, Auburn (USA); Silvia Mazzetto, Lebanese American University, Byblos (Libano); Manlio Michieletto, University of Rwanda, Kigali (Ruanda); Francesco Polesello, Azm University, Tripoli (Libano); Alessandra Ponte, Université de Montréal, Montréal (Canada); Nikos Skoutèlis, Technical University of Crete, Chania (Grecia); Gianni Talamini, City University of Hong Kong, Hong Kong (Cina); Guido Zuliani, The Cooper Union, New York (USA), Maria Gatto, Ufficio Relazioni Internazionali Università Iuav di Venezia, Clara Grano, Agenzia Erasmus+ INDIRE. \nI materiali digitali di Iuav Abroad sono disponibili su: http://www.iuav.it/Ateneo1/chi-siamo/Iuav-Acade/
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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 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".