“Wiinge chi-baapinizi geniin ode: It really makes my heart laugh”: Language, culture, identity, and urban language revitalization
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.
Bibliographic record
Abstract
In Canada, the majority of Indigenous people live off-reserve in urban centres. Living offreserve is a risk factor for language loss, as indicated by the fact that 44.9 percent of First Nations people on-reserve are able to conduct a conversation in an Aboriginal language, compared to only 13.4 percent of First Nations people off-reserve (Statistics Canada, 2019). For this reason, urban language revitalization is vital, yet it remains understudied and underfunded The Kingston Indigenous Languages Nest (KILN) is an example of grassroots urban language revitalization. KILN presents Indigenous families in Kingston, Ontario, with opportunities to access language and culture through weekend family-focused sessions, as well as immersion weekends, evening adult language classes, digital resource development, and community partnerships focused primarily on Anishinaabemowin, Kanien'kha, and Cree. Using qualitative data collected through talking circles, I explore what effect the weekend sessions have on participants' lives. The results indicate that participation improves language use. However, its impact stretches beyond this; participants describe a deepening of their cultural understanding and connection to community as key parts of the development of their identities as urban Indigenous people. It is clear that culture-based pedagogy is central to both language survivance and cultural and identity growth. It deepens participants' understanding of themselves as urban Indigenous people, allows them to experience their culture as a way of life, creates new understandings of Indigenous identity and community, and validates their community identity as equal to other Indigenous ways of being.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it