Bibliographic record
Abstract
The McMaster University conference, seeking "new possible directions for Italian-Canadian Studies in the new millennium," presents a critical challenge.Italian-Canadians are now integrated into a Canadian life that attracts new waves of immigrants (and refugees) from varied locales, primarily Asia and Africa.The Italian government has realized this and in order to maintain contact with its diasporas, has offered various legal ways to stay connected.For the current generation of Italian Canadians, connection means the practicality of obtaining Italian citizenship (in addition to Canadian) as a means of legal access to work and live in the European Union.The current state of Italian-Canadian Studies, in my opinion, is pre-occupied with survival.In this context, examining how Italian immigrants moved to the mainstream may indicate a direction for Italian-Canadian Studies.The conference keynote speaker, Damiano Pietropaolo, spoke of the hyphen in the term, "Italian-Canadian," as a bridge between the two countries.I did not meet the "hyphen" until I moved to Toronto as an adult.Born and raised in Calgary, I grew up without the hyphen.Make no mistake, I was keenly aware of my Italian heritage, having lived for nearly eight years above my father's Italian restaurant, La Villa.I should mention that my mother was not Italian; she was born in the United States of German parents, who had migrated from the Black Sea
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.017 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".