OF THE REQUIREMENTS FOR THE DEGREE OF
Bibliographic record
Abstract
Aboriginal language revitalization is complex and challenging. Sixteen research participants talked with me about competing priorities for urban Aboriginal individuals and families, the linguistic diversity of the British Columbia First Nations, and how demographic urbanization of Aboriginal peoples intersects with movements of language revitalization. The resulting analysis highlights some emerging language ideologies connected to urban Aboriginal language use and learning. Language ideologies have been defined as “the cultural system of ideas about social and linguistic relationships, together with their loading of moral and political interests ” (Irvine, cited in Kroskrity 2000:5). By identifying some commonalities in research participants ’ attitudes around Aboriginal languages in the city, I argue that ‘placing language ’ and ‘finding a place for language ’ are critical issues for looking at Aboriginal language use and learning in Vancouver. By ‘placing language’, I mean that participants stressed the locality of Aboriginal languages, drawing important connections between land and language. Many honoured local languages by stating that their use and preservation should be top priorities in urban-specific language revitalization initiatives. They also recognized that other Native languages are represented in the city and could be fostered by collaboration with home communities, including reserve language programs. By ‘finding a place for language’, I mean taking time and making effort toward language learning and use in the fast-paced
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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 | 0.013 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.021 |
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".