‘We are slowly reclaiming for ourselves’: the generative possibilities of Indigenous youth voices
Bibliographic record
Abstract
Indigenous youth are actors of change in their communities, providing new perspectives on decolonization, unity, and cultural resurgence within the spaces they occupy. In this article, we report on a collaborative study that examined the many layers of Indigenous youth voices. With an organization that represents First Nations youth in Quebec, we conducted an Indigenous mixed methods study combining key informant interviews, a survey, and online group conversations. Four defining characteristics of Indigenous youth voices came to light: (a) hopeful and passionate, yet restricted; (b) disregarded in formal political structures that are unwelcoming and resistant to change; (c) strong with possibilities; and (d) inherently embedded in the collective. These characteristics highlight the vibrancy of Indigenous youth voices as they seek to generate forms of expression that reflect their realities, knowledges, and fluid identities. Our research points to the inadequacy of conventional politics and perspectives that emphasize the individual and the need for promoting alternative and intersectional modes of expression that provide meaningful and influential supports and spaces. These manifestations of youth survivance underscore pathways of resurgence that are culturally rooted. In these decolonial practices, young people seek to embrace these complexities and reclaim who they are.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".