Language maintenance-attrition among generations of the Venetian-Italian community in Anglophone Canada
Bibliographic record
Abstract
This study reports on language contact phenomena among the Italian-Venetian communities of Anglophone Canada. The analysis perspective is twofold: on one hand it studies language maintenance/attrition comparing two cohorts of migrants, those already well researched who migrated during the period of mass migration (1945-1967) and those who did so in the following four decades (1970-2009). On the other, it investigates language maintenance/attrition taking an intergenerational perspective on three generations of speakers. The corpus used in the analysis is composed of 56 interviews, collected during three months of fieldwork in Canada in 2009. These data were supplemented by 99 questionnaires, which set the background of the analysis, discussing in particular the linguistic habits and attitudes of the community investigated. Given the huge amount of data considered and the mainly quantitative approach taken in this research, two statistical software programs, Taltac and SPSS, were employed to help with the analysis. Another tool, meta-linguistic observation, is also used to broaden the general framework of the study and whenever possible support it with more evidence. The literature on language maintenance/attrition among Italian migrant communities is sizeable; however, there remains room for further investigations. This work, in particular, addresses two major aspects still rarely explored: first, quantifying the decline in heritage language skills on a generational scale, and secondly, comparing the linguistic skills of post-Second World War migrants, on which research has mostly concentrated so far, with those of new waves of migrants. Although this thesis is concerned with a particular geographical and historical framework and the findings are therefore representative of this specific context, the work aims to point to some observations from which generalisation may be possible. By setting side by side these two very distinct cohorts and discussing the new linguistic tendencies in language proficiency among the most recent groups of migrants, research is opened to the new scenarios evolving among Italian communities abroad.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".