Conflict and Italian-Canadian Literature: Problems in Theory and Practice presented at the Italian-Canadian Literature Conference in Toronto, ON, November 14-16, 2008
Bibliographic record
Abstract
The A&PDF award enabled me to go to the University of Toronto and give a paper \nat a conference. I am submitting a copy of the paper with this report. The conference helps to support my research work in ethnic minority writing and my teaching in graduate and undergraduate courses. \n \nDr. Joe Pivato of the Centre for Language and Literature spoke at the conference, Envisioning Culture: Evolving Writing and Community hosted by the Frank Iacoducci Centre for Italian-Canadian Studies, University of Toronto. This November, 2008, event was the 12 biennial conference of the Association of Italian-Canadian Writers. Joe spoke on a panel discussion with novelists Frank Paci and Caterina Edwards, and the following day gave an academic paper on “Conflict and Italian-Canadian Literature: Problems in Theory and Practice.” \n \nJoe is editing a book of essays on Pier Giorgio Di Cicco, Poet Laureate of Toronto.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.051 | 0.024 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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; 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".