Fostering relationships and envisioning future : Kluane First Nation final agreements and transmission of overlap knowledge
Bibliographic record
Abstract
This research addresses the unique political landscape of Yukon First Nations including the imposition of the Indian Act, historical relocation of First Nations, and the impact of land claims agreements and modern treaties in Yukon. Two First Nations, Kluane FN and White River FN, have completely overlapped Traditional Territories. Kluane FN ratified their land claims agreement in 2003, while White River FN remains an Indian Act Band. In this context, I interviewed four Kluane Knowledge Keepers, all who directly negotiated and implemented Kluane FN land claim agreements. I did this to understand the development of land claims and self-government in the Kluane area. Focusing on intergenerational knowledge transfer, I used interviews to build a foundation of knowledge about the progression of land claims in Kluane including impacts on relationships between White River FN / Kluane FN governments stemming from the amalgamation. The Knowledge Keepers I interviewed had a profound desire to share their knowledge with Kluane Youth about why Kluane People have chosen this path. Land claims as understood through the Knowledge Holder interviews produced several key themes: implementation, negotiation, amalgamation / de-amalgamation, citizen engagement, relationships / conflict resolution, overlap, culture, Elders / Youth. I synthesised one story from each of the four interviews to exemplify different perspectives regarding the implementation of land claims using the most notable implementation challenge for Kluane FN, the 100 percent overlap. I then completed two focus group discussions with two Kluane Youth to establish their base land claims comprehension, before sharing with them the history behind land claims through the stories of the Knowledge Keepers. Then, as a group, we imagined fundamental components of an ideal future for Kluane People. My research created the conditions for Youth to use storytelling to deepen their relationships to the implementation of land claims in Kluane growing their collective leadership potential. The primary outcome of my research is that Youth can use this information about land claims and reflections from their engagement with this research process to imagine an ideal future for Kluane FN grounded in Kluane histories.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".