Bibliographic record
Abstract
This qualitative study introduces a variety of considerations to help understand ways in which Indigenous Knowledge broadens the existing dominant views of leadership. Indigenous Elders, as a source of Indigenous Knowledge provide intergenerational leadership through the sharing of their teachings, oral histories and experiences. For this study I examined the culturally relevant Indigenous leadership program that is offered within the non-credit Longhouse Leadership Program (LLP) at the First Nations House of Learning (FNHL) at the University of British Columbia (UBC), taught by Elders, cultural leaders and educators. Through the telling of oral histories, nine Elders and cultural educators who work with the FNHL community shared their views on Indigenous leadership presenting historical examples of Indigenous leadership and recommending pedagogy for the current Longhouse leadership program. Their cultural teachings are resources for Indigenous leadership pedagogy that is transformative. The Elders’ teachings on Indigenous leadership are transformational because they identify and deconstruct colonial structures and support the self determined leadership goals of local communities. The teachings are: knowing the history of the land and educating others; reclaiming culture and living the teachings; culture as a support for individuals, families and communities; leadership as a gift-step forward demonstrating community responsibilities; and wholistic pedagogy all which is transformational when delivered within an anti racism education framework. These teachings are consistent with those found more generally in the academic literature, emphasizing leadership grounded in the cultural teachings that supports living Aboriginal communities and coalition building for change. [An errata to this thesis/dissertation was made available on 2013-03-21.]
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".