Bibliographic record
Abstract
SEBASTIANO AGLIECO is an independent scholar from Monza, Italy. Poet and literary critic, his books include: Giornata (La Vita Felice 2003), Dolore della casa (Il Ponte del Sale 2006), Nella storia (Aìsara 2009), Radici delle isole (La Vita Felice 2009), Compitu re vivi (Il Ponte del Sale 2013), Infanzia resa (Il Leggio 2018), and Casa delle lucertole (Libraccio Editore 2019). He also co-edited (with Luigi Cannillo and Nino Iacovella) the volume Passione Poesia. Letture di poesia contemporanea 1990-2015 (CFR 2016). narcyso@virgilio.itFABIO BATTISTA is completing his Ph.D. in Comparative Literature at The Graduate Center, CUNY and is the recipient of an Andrew W. Mellon/ACLS Dissertation Fellowship (2018-2019). His project, Staging English Affairs in Early Modern Italy: Gender, Politics, Intercultural Communication, 1590-1690, traces the presence of English socio-political history in 17th-century Italian drama. fbattista@gradcenter.cuny.eduROBERTA COLOMBI is Professor of Italian Literature at Roma Tre University. Her scholarly interests focus upon the 17th-century novel, the humorous 19th-century prose, and Ippolito Nievo and the historical novel. Her book publications include: Lo sguardo che “s'interna”. Personaggi e immaginario interiore nel romanzo italiano del Seicento (2002), Ottocento stravagante. Umorismo, satira e parodia tra Risorgimento ed Italia Unita (2011), and Un umorista in maschera. La narrativa di Antonio Ghislanzoni 1824-1893 (2012). Colombi has also published several articles on Pirandello, Gadda, Palazzeschi, and Svevo. roberta.colombi@uniroma3.itCLORINDA DONATO is the George L. Graziadio Chair of Italian Studies at California State University, Long Beach, where she is Professor of French and Italian. She researches and publishes in the fields of 17th-century studies, Intercomprehension, and translation. She was the Principal Investigator for the NEH-project: “French and Italian for Spanish Speakers” (2012-2015). Clorinda.Donato@csulb.eduELISA FIORENZA has a research grant from Roma Tre University (Department of Foreign Languages, Literatures and Cultures), where she obtained a Ph.D. in Didactics of Modern Languages and an M.A. in Language Sciences. Her main fields of interest are language didactics and Intercomprehension in Romance languages. elisa.fiorenza@uniroma3.itDANIELE FIORETTI is Assistant Teaching Professor at Miami University, Ohio. He received a Dottorato di Ricerca in Italianistica from the University of Florence, and a Ph.D. in Italian from the University of Wisconsin-Madison. He is mainly interested in Italian modern and contemporary literature, cinema and culture. His publications include: Utopia and Dystopia in Postwar Italian Literature – Pasolini, Calvino, Sanguineti, Volponi (2017); Carte di fabbrica: la narrativa industriale in Italia 1934-1989 (2013); and Paolo Volponi, Scrivo a te come guardandomi allo specchio. Lettere a Pasolini 1954-1975 (2009). To his credit he has also articles on Pasolini, Volponi, Minervini, Blasetti, and others. fioretd@miamioh.eduMANUELA MARCHESINI is Associate Professor of Italian at Texas A&M University. Her research centers on questions of method, interpretation, and aesthetic value. Her books include: La galleria interiore dell'Ingegnere (2014), which offers a reassessment of Gadda's Pasticciaccio by exploring the role played in the novel by the figurative arts and by Dante's Comedy; Scrittori in funzione d'altro: Contini, Longhi, Gadda (2005); and Filosofia dei mondi globali. Conversazioni con Giacomo Marramao (2017, co-edited with Stefano Franchi). She has also published critical essays on Manzoni, Boccaccio, Pizzuto and Beckett, Collodi and Bene, Bellocchio and Serra, and Moresco. mmarchesini@tamu.eduDIEGO SBACCHI is currently a secondary school teacher of Italian and Latin Languages and Literatures in Macerata, Italy. He earned a Ph.D. in Italian Studies from the University of Toronto and he is about to complete a second Ph.D. in Italian Literature at the University of Bern. He studies the influence of Pseudo-Dionysius on Dante's work, and is author of articles on Dante, Petrarch, Ungaretti, Ariosto, and Tasso. dsbacchi@chass.utoronto.ca
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.528 | 0.354 |
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; the direct Gemma label and the distilled Codex classifier 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".