Language, Identity, and Cultural Awareness in Spanish-speaking Families
Bibliographic record
Abstract
There exists a wealth of research in the areas of heritage languages in the United States. Over the last two decades, the rapidly growing work on Spanish, particularly, is making important strides in the understanding of this research area. Yet, there is only minimal work focusing specifically on language socialization and Spanish maintenance in Canada. In this article, I describe qualitative research examining the contextual factors of the linguistic socialization of Spanish-speaking families and their children in Vancouver, Canada. Analysis of the data indicates that cultural awareness and identity, familism, and home language practices are key factors that cut across a variety of aspects of first language maintenance, both as agents and outcomes. Il existe une riche base de recherche sur les apprenants de langues d'origine aux Etats-Unis. Lors des deux dernières décennies, des études sur l'espagnol en particulier, ont permis de grands progrès dans ce domaine d'étude. Néanmoins, le nombre de recherches examinant la situation canadienne vis-à-vis de la socialisation linguistique et le maintien de l'espagnol reste infime. Cet article rapporte les résultats d'une étude qualitative, laquelle examine les facteurs contextuels de la socialisation linguistique de familles et de leurs enfants de langue espagnole à Vancouver au Canada. L'analyse des données indique que la conscience culturelle et l'identité, le famillisme, et les habitudes linguistiques au foyer sont des facteurs critiques qui affectent une variété d'aspects du maintien de la langue maternelle, autant comme agents que comme conséquences.
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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 | 0.002 | 0.005 |
| 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 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".