Restoring Our Roots: Land-Based Community by and for Indigenous Youth
Bibliographic record
Abstract
Knowledge gathered about the impacts of land-based teachings on Indigenous youth is limited. Many Indigenous people and government commissions have pointed to targeted assimilation and land theft as central to historical and ongoing collective dissociation of Indigenous Peoples from their ways of being in relation with the land. It is thus paramount that Indigenous youth be given the opportunities to (re)connect with their cultures in safe, accessible spaces/places. Demonstrating the many ways learning from the land is beneficial for Indigenous youth, the Restoring Our Roots participatory action research project contributes to the knowledge base in this area to centre Indigeneity and reclaim our cultures by enacting Indigenous methodologies and pedagogies. An Indigenous youth advisory committee developed a four-day land-based retreat, held in July 2018, that focused on (re)connecting Indigenous youth to land-based teachings and ceremony. In interviews following the retreat, youth participants spoke about positive changes related to identity, belonging, well-being, and feeling free from violence in this space that engaged land-based teachings led by Elders, Knowledge Holders, and youth themselves. Some Indigenous youth who identify as Two-Spirit, non-binary, and/or LGBTQIA+ attended the retreat and shared how important it is to have safe spaces that are inclusive of diverse gender roles and identities. Restoring Our Roots created an inclusive community of support, sharing, and learning for Indigenous youth, extending into participants’ everyday lives in the city. This project has since grown into Land As Our Teacher, a five- year research project funded by the Social Sciences and Humanities Research Council of Canada, that explores benefits of land-based pedagogies for Indigenous youth.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".