hiił kʷiiʔił siƛ (bringing something good from way back) : a journey to humanize post-secondary education
Bibliographic record
Abstract
This dissertation explores my personal journey of becoming a human being, particularly by drawing on Nuu-chah-nulth principles of ʔuuʔuuqʷaač̓ii (self-independence). Relevant literature, resources and personal stories help identify the underpinning aspects of epistemological dominance, blindness, and collisions, which occur in the classrooms of post-secondary institutions. Although Indigenous-led education and policy contributes to Indigenous student success, more has to be done to understand current processes of Indigenization, decolonization, and reconciliation. Educational practitioners, Indigenous and non-Indigenous, who engage in these processes help lead the way, but will likely encounter feelings of being unsettled or uncomfortable. At times, feelings of fear, shame and guilt arise leaving people feeling unsure or unwilling to try. Nuu-chah-nulth teachings of yaʔakmis (love and pain) represents the possibilities and limitations of integrating Indigenous ways of knowing and being within post-secondary. Indigenization, reconciliation, and decolonization are all processes that require courage and action; they also require leaders who are ready for these processes. They also require an understanding of one’s self in relation to values, beliefs, and prejudices; it is a critical component of these processes. Leaders must be genuine while recognizing the value of Indigenization, decolonization, and reconciliation. The research questions are designed to bring a holistic approach and provide guidance that will help to improve my practice, as an educator. The research questions are, • What do the principles of Indigenous self-determination mean in the context of indigenizing initiatives within post-secondary education? • What are the possibilities and limitations (the love and pain)? • What needs to change in order for these principles to be realized in these initiatives? Throughout this journey, my personal life experiences, as Nuu-chah-nulth-aht (person of Nuu-chah-nulth ancestry), inform and help me unmask favorable and unfavorable practices, specifically of Indigenization. The findings reveal the uncomfortable nature many feel when confronted with the history of Canada and the daunting task of Indigenization, decolonization, and reconciliation. Unpacking colonial policies and practices of education while examining more closely aspects of who we are (values, beliefs and prejudices), particularly as people who share this land, is a critical component of doing the work of Indigenization, decolonization, and reconciliation.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.027 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".