Changing orientations to heritage language: The practice-based ideology of Sri Lankan Tamil diaspora families
Bibliographic record
Abstract
Abstract The notion of heritage language (HL) has recently been challenged by emerging orientations to language. That languages are always in contact, they are constructed by ideologies, and they don’t have an ontological status challenge traditional notions of HL as primordial, pure, and territorialized. In this article, I draw from data from a qualitative inquiry adopting observations, surveys, and interviews on how families of the Sri Lankan Tamil diaspora community in UK, USA, and Canada define heritage language and competence. I focus specifically on interview data to unveil the language ideologies of community members relating to heritage language and identity. For them, competence means having the ability to align Tamil verbal resources strategically with multimodal semiotic resources and spatial repertoires to accomplish social and cultural communicative activities. For this objective, being proficient in fragmentary verbal resources, receptive and/or conversational skills, low diglossic Tamil, and informal register are deemed satisfactory. Therefore the corpus that is considered as HL is also changing in diaspora contexts to accommodate appropriations from other languages, and metonymic uses, which develop shared indexicality for the community. I label these assumptions as constituting a practice-based ideology of HL. Such an orientation will help us understand HL as a socially constructed and changing construct, while affirming its importance for migrant communities.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".