From Mass immigration to Professional Workers. A Portrait of the Present Italian “Comunità” in Ontario, Canada
Bibliographic record
Abstract
The history of Italian migration to Canada has been extensively analyzed.However, after the 1990s its most recent developments have not been as well documented.This study!explores the transformation of the Italian community in Ontario in the last thirty years, arguing that although they do not relate to the older immigrants, the "global-digital immigrants" that emigrated after the 90s still recreate extended families and organizations to help keep their Italian identity.The research starts retracing the history of Italian immigration to Canada and then compares the old and new immigration waves.To complete the picture, data of the Italian immigration in Ontario are examined, as well as immigration laws and the role of the Italian language in the Canadian context.Further studies are also suggested.The identities of individuals and groups within specific diasporas, as Karim Karim notes, are formed by complex historical, social, and cultural dynamics specific to the group and by its relationships with other groups.Therefore, it is valuable to determine the characteristics of each diasporic group, including retention of ancestral customs, language, religion, marriage patterns of its members, and particularly the ease of communication between various parts of each transnational group (Karim 3). History of Italian immigration to CanadaThe Italian, like the Irishman, is a bundle of contradictions.He is hot-headed and quick-tempered; yet he is good-natured, kind, obliging; he is gay, fun-loving, light-hearted: yet he takes the every-day duties of life as seriously as he takes religion; he is generous and yet will deny himself the necessities of life to save money.Hot-blooded, volatile, when compared with the Anglo-Saxon, artistic in temperament, industrious, easily influenced for good or bad, the Italian immigrant is an interesting addition to our population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".