Youth response to climate change: Learning from Indigenous land-based camp at the Northern Saskatchewan Indigenous Communities, Canada
Bibliographic record
Abstract
This paper represents Youth's involvement in land-based learning in Indigenous culture camps (LLICP) in a powerful and innovative approach to addressing the pressing global issue of climate change. Following Indigenist and relational approaches, we (Indigenous and non-Indigenous youth and educators) explore the critical aspects of this initiative, highlighting its significance and potential impact. Indigenous communities have long held a deep connection with the land and possess traditional knowledge that is invaluable in combating climate change. The LLICP initiative involves organizing cultural camps designed for youth from diverse backgrounds to learn from Indigenous elders and community leaders about the vital relationship between the environment and Indigenous cultures. The LLICP provides a unique opportunity for young people to engage with Indigenous wisdom, traditional practices, and land-based teachings. Through Indigenous elders and knowledge-keepers guidelines, we learned a holistic understanding of sustainable living, biodiversity conservation, and the importance of preserving ecosystems. Our learning helped us, particularly our youths, to become proactive stewards of the environment and advocates for climate action. The LLICP fosters cross-cultural understanding and collaboration, encouraging a sense of unity among youths. The LLICP inspires innovative solutions to climate-related challenges and empowers youth to take leadership roles in their communities, advocating for sustainable policies and practices. The LLICP offers a powerful means of engaging young people in the fight against climate change while respecting and honoring Indigenous knowledge and heritage. It is a promising step towards a more sustainable and resilient future for all.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".