Videographic, Musical, and Linguistic Partnerships for Decolonization: Engaging with Place-Based Articulations of Indigenous Identity and Wâhkôhtowin
Bibliographic record
Abstract
N’we Jinan, a group of young Indigenous artists who run a mobile production studio and an integrative arts studio, travel to different Indigenous communities, where they support youth in writing and recording music that involves the local community. N’we Jinan employs social media to articulate and protect Indigeneity through the sharing of Indigenous music videos, empowering youth to resist continued colonization. These videos serve to create a sense of connection in Indigenous communities in Turtle Island (Canada) as well as offer a means by which non-Indigenous listeners can learn about contemporary Indigenous cultures. Viewed in conjunction with Nunavut’s Inuit Qaujimajatuqangit and the Northwest Territories’ Dene Kede and Inuuqatigiit, which provide a framework of traditional knowledge, values, and skills specific to Indigenous communities in the Canadian Arctic, the texts implicitly invite non-Indigenous listeners’ engagement in social justice activism as settler allies. The texts invite listening to and viewing the empowering songwriting and recording practices through the lens of social justice and wâhkôhtowin or kinship relations, which involves walking together (Indigenous and settler) in a good way and engaging with Bourdieu’s influential framework of cultural capital. The themes explored in the songs include cultural identity, language, and self-acceptance. The empowering songs of N’we Jinan are place-based articulations of identity that resist coloniality and serve as calls to action, creating embodied videographic, musical, and linguistic partnerships that serve as important articulations of Indigenous identity and which promote the decolonization of reading and listening practices and, by extension, education.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".