After exile : heritage language and literacy socialization across three generations in one Chilean-Canadian family
Bibliographic record
Abstract
Global migration is increasingly driven by experiences of extreme social, political, economic, and environmental adversity (UNHCR, 2019)—experiences which become part of families’ personal and cultural narratives. However, such narratives are routinely marginalized in formal learning contexts (e.g., Campano, 2007; Marshall & Toohey, 2010), even though they may constitute a key part of students’ identities and connection to the language/s and culture/s of their heritage (Avineri, 2019; Becker, 2013, 2014). In recent decades, modern language education scholars have begun to call for the more explicit integration of historical and political knowledge when conceptualizing culture in language teaching (Byram & Kramsch, 2008; Freadman, 2014), but it appears that the field of heritage language education has yet to enter these conversations. Guided by theories of language socialization (Ochs & Schieffelin, 1984, 2017), syncretic literacy (e.g., Duranti & Ochs, 1996), and difficult knowledge (e.g., Pitt & Britzman, 2003), in this year-long ethnographic case study, I examined the language and literacy socialization of difficult cultural knowledge across three generations in one Chilean-Canadian family: the Calfus (pseudonym). The grandparents had come to Canada as refugees in the 1970s fleeing the Pinochet regime in Chile. Their grandchildren (ages 7 and 9) were learning their heritage language at home and in a Spanish-English bilingual program at school. I used thematic (Saldaña, 2013) and narrative (Ochs & Capps, 2001) methods to analyze data from multiple sources, including interviews, audio recordings, field notes, and photos of student work. I also examined how adults made use of IRE (initiation, response, evaluation) routines to manage difficult historical topics when talking with children. Overall, the analysis demonstrated the salience and significance of difficult cultural knowledge in the Calfu family’s language and literacy socialization practices outside of school, the children’s dynamic and shifting sense of imagined transnationalism, and the ways that Indigenous identities can be eclipsed by Hispanic identities in Spanish language programs (e.g., Calderón & Urrieta, 2019). Nevertheless, the children consistently demonstrated highly creative and agentive ways to claim authorship and ownership of their difficult cultural knowledge. The study has significant implications for teaching heritage language learners in post-exile contexts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".