Tlʼe chin Trʼe je l : coming together to explore our Trʼonde k Hwe chʼin epistemology of leadership
Bibliographic record
Abstract
The Trʼondëk Hwëchʼin people have a rich history connected to land and people, at the confluence of the Klondike and Yukon Rivers. This study explored our Trʼondëk Hwëchʼin epistemology of leadership in hopes of applying its findings to transformative change in educational leadership in our community, in the current public school system. The use of a Critical Theory framework and the application of a combination of Participatory Action Research and an Indigenous Research Methodology, allowed me as a Trʼondëk Hwëchʼin citizen to respectfully ask Elders and Knowledge Holders to collaborate with me in this research. Through multigenerational focus groups, we engaged in conversation around leadership, decision making and values that guide us as Trʼondëk Hwëchʼin citizens. Conversations centered around cooperative decision making cradled in caring, respectful relationships among multi-generational members of community. Stories were shared of how knowledge and responsibility are passed down through listening, reciprocity and mentorship and how all of these relationships are deeply tied to place.
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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 | 0.003 | 0.004 |
| 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 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".