Kaykwy Wii Ooshihtaayen Dimayn? What Will You Do Tomorrow? Strengthening Indigenous Leadership Capacity to Influence School Culture and Student Achievement
Bibliographic record
Abstract
There continues to be a dichotomy that exists between Indigenous and non-Indigenous academic success within Canada. Within a public education context, this Dissertation-in-Practice (DiP) will address how the lack of preparation for school leaders to effectively incorporate Indigenous leadership approaches, impacts the ability to positively support school culture and achievement for Indigenous youth. Focusing specifically on the Truth and Reconciliation Committee Calls to Action 62 and 63, this DiP will explore the ways in which leaders in schools can support the inclusion of Indigenous ways of knowing within their leadership roles. Existing within a critical paradigm, the DiP will incorporate transformative and Two-Eyed Seeing leadership approaches to develop shared leadership capacity for the development of Indigenous leadership approaches. Structuring the change using a model that represents both western and Indigenous ways of knows is an essential component of the work through an integrated framework that includes the change path model and Circle of Courage. The DiP outlines multiple potential solutions to address the Problem of Practice including professional learning networks, Sharing Circles and collaboration with Elders. While all potential solutions provide endless possibilities, the use of Sharing Circles is identified as the preferred solution. Both the change path model and the Circle of Courage prioritize the need for belonging and relationships which are fostered by creating authentic opportunities for all members of schools and community to share their voices. Keywords: TRC, Calls to Action, Two-Eyed Seeing, transformative leadership, Circle of Courage, Sharing Circles
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".