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Record W4407683003 · doi:10.1515/applirev-2023-0244

Playing with funds of difficult knowledge: interactional insights for heritage language education

2025· article· en· W4407683003 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueApplied Linguistics Review · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council
KeywordsHeritage languageApplied linguisticsPsychologyLinguisticsSociologyPedagogyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Migration stories are at the heart of how many immigrant-background Heritage Language Learners (HLLs) construct a sense of home, community, and identity across spatiotemporal scales. Nevertheless, narratives containing difficult knowledge (e.g., about war) are generally seen as threats to, rather than as assets in language learning and in education more broadly, and as such, are rarely drawn on in classrooms. In this paper I analyse excerpts from a group interview that I conducted with four grade-four girls during a year-long ethnographic case study. In particular, I examine how we all used various linguistic and paralingiustic resources to construct play frames . The play frames created a lower-stakes space in which to navigate the emotionally complex cultural memories that my interview questions about origins and migration prompted. The findings have implications for how language teachers listen to and engage with their HLLs’ funds of difficult knowledge.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.316
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it