Bibliographic record
Abstract
Canada is home to millions of immigrants from diverse origins and backgrounds, and yet there is limited research on the country's growing population of minority language groups.As a human labor export site, the Philippines continues to be a top source of one of the largest migrant groups in the host nation in recent years, but very little is known about the consequences of the diasporic movement on Philippine heritage languages.This mixed methods research investigates the minority language maintenance of selected Yogad families in Canada.In Phase 1, narratives from various household types were explored to identify existing language practices, beliefs, and management strategies among Filipino migrant homes of Indigenous heritage, framed within Spolsky's (2004) language policy model, as well as Giles and Coupland's (1991) Communication Accommodation Theory.The lived experiences from the parent and caregiver generation reflect integrative patterns towards the host environment and community recognition, while accounts from children point to restorative themes in approaching heritage language sustenance.To further examine the present linguistic situation of the Yogad language group, Giles et al.'s (1977) Ethnolinguistic Vitality Theory and Landweer's (2016) Indicators of Ethnolinguistic Vitality were both implemented at the community level.A key discovery in Phase 2 is that while the indicator scores indicate a similar degree of urgency for language intervention in the host and home country settings, the emerging presence of the Yogad community in the digital space could not be accounted for by the current vitality construct.Merging the qualitative data from Phase 1 and the quantitative data from Phase 2, the study presents a working model for Yogad language maintenance in Canada.The findings of this work define the necessary groundwork relevant to the establishment of future revitalization efforts for Yogad, to promote the continuous use of an endangered language in migrant spaces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".