‘He Apiti Hono, He Tātai Hono’: Ancestral Leadership, Cyclical Learning and the Eternal Continuity of Leadership
Bibliographic record
Abstract
This research developed out of a fascination with leadership as a personally intuitive experience growing up in Vancouver, Canada, and observing my father. I saw in him a translation of our Indigenous Stό:lō values and knowledge that he learned growing up with his grandmother (my great grandmother) on our Indian reserve lands and applied to the complexities of contemporary life that were presented to him in the city. Dad’s responsibilities have always required him to attend to our Indigenous community’s social and political relations, to negotiate personal and professional boundaries in work and to maintain balance between individual fulfilment and family obligations. What I saw beneath his contemplations around these often competing responsibilities was a point of reference that guided his decisions and actions. He draws upon our Stό:lō cultural values that he learned in his early life to guide moral and ethical behaviour and decision-making. Those values transfer through his own life, but also through ours as his children.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".