Bibliographic record
Abstract
This paper examines some aspects of language contact in a Croatian-English bilingual speech community in Canada.The primary goal of the paper is to better understand language proficiency, language use, and attitudes of second-generation heritage speakers of Croatian.In officially multicultural Canada, the roles of Croatian and English are both complementary and distinct.Indeed, there is an obvious imbalance in the position and use of the two languages.Whereas English functions as a dominant or majority language (one of the two official languages), Croatian is a heritage or minority language.Although many studies have been conducted on different heritage languages, little attention has been paid to Croatian as an immigrant heritage language in Canada.Therefore, a closer examination of heritage language development and practices in this bilingual speech community is necessary.The research presented here is based on data from two sources: the Canadian census data and the data from a sociolinguistic survey conducted in the Croatian community in the greater Toronto area through a questionnaire.In order to describe linguistic practices in the community and create a linguistic profile of the second-generation heritage speaker of Croatian, the study focuses on the following issues: the acquisition of language skills in English and Croatian, the use of the two languages in everyday life, the learning of the heritage language, and attitudes towards maintenance of the heritage language.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".