Language and literacy development in a Canadian native community: Halq'eméylem revitalization in a Stó:lō head start program in British Columbia
Bibliographic record
Abstract
ABSTRACT The following study is part of a larger community‐based project that began in 2007 to document Halq'eméylem language and cultural transmission among Elders, family members, and teachers in the Stó:lō First Nation located in Chilliwack, British Columbia, Canada (MacDonald et al., 2010; MacDonald et al., 2011). Within the larger project, this article focuses on Halq'eméylem language and literacy transmission and the ways that literacy practices, including the creation of a Halq'eméylem orthography, and theories of school‐based second language acquisition have influenced language revitalization within a British Columbia Aboriginal Head Start program. Using ethnographic methods and grounded theory, findings illustrate how a lack of teacher fluency has influenced the transmission of Halq'eméylem by creating the need to rely on a unique bi‐/multiliteracy base where environmental print, translated names, translated songs, and interactive text‐based computer games are used to support Halq'eméylem language development among parents and teachers who are jointly and concurrently learning and teaching their ancestral language. The study is anchored in a critical perspective on multilingualism (Creese & Blackledge, 2010) that moves away from ideologized beliefs that linguistic systems should be strictly separated, including within second language classrooms (Cummins, 2008; Lüdi, 2003; Lüdi & Py, 2009; Moore & Gajo, 2009; Swain & Lapkin, 2005).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".