Heritage language classes and bilingual competence: the case of Albanian immigrant children in Greece
Bibliographic record
Abstract
The present paper reports on a questionnaire survey conducted in the course of a broader research project on bilingualism (BALED). It compares two groups of Albanian immigrant parents in Greece with respect to their practices for supporting minority language development. The first group includes parents (N = 35) whose children receive systematic instruction in the heritage language; the other group (N = 167) comprises parents who do not send their children to heritage language classes but may support Albanian language maintenance in various ways. Αccording to their parents’ reports, all children were dominant in Greek. Our purpose was to compare the two groups with regard to (i) language use patterns among family members, (ii) parental practices in support of the minority and the majority language, and (iii) children’s language competence in the respective languages. Τhe ultimate aim is to explore the relations between parental practices and children’s competence in the minority language. Results indicated that parents who send their children to heritage language courses also engage more often in practices which promote literacy in the heritage language at home. These children were reported by their parents to possess literacy skills in Albanian to a higher degree than children who do not attend systematic instruction in this language. Our findings corroborate previous research (e.g. Bylund, E., and M. Díaz. 2012. “The Effects of Heritage Language Instruction on First Language Proficiency: A Psycholinguistic Perspective.” International Journal of Bilingual Education and Bilingualism 15 (5): 593–609; Chumank-Horbatsch, R. 1999. “Language Change in the Ukranian Home: From Transmission to Maintenance to the Beginnings of Loss.” Canadian Ethnic Studies Journal 31 (2): 61–75; Schwartz, M. 2008. “Exploring the Relationship between family Language Policy and Heritage Language Knowledge among Second Generation Russian-Jewish Immigrants in Israel.” Journal of Multilingual and Multicultural Development 29 (5): 400–418) suggesting that literacy development at home and especially attendance of heritage language instruction are extremely beneficial for its development without disrupting the development of the majority language.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".