Bibliographic record
Abstract
The writing of Italian-Canadian authors indicates a profound awareness of history. This is not the history of textbooks or university courses but real past experiences imprinted on the consciousness of immigrants and their children. Often this family memory extends back to grandparents and recalls the harsh conditions of separated families, of husbands and wives living apart for long periods of time, of family members in different continents. Nowhere is the long term effects of this history more evident than in the writing of women writers of immigrant background. Mary di Michele remembers her grandfather's migration to Canada for work in A Streetcar Named Nostalgia, Maria Ardizzi uses early Italian migration as a subtheme in her novels, and Dorina Michelutti depicts a grandmother haunted by this dark memory. Immigration history has been long neglected by traditional Canadian historians and, it seems, we must turn to the writers for views of an almost forgotten past.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.032 | 0.007 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".