Who Am I and What Is My Role in Reconciliation with Indigenous Peoples?
Bibliographic record
Abstract
This paper reports on an auto ethnographic examination of my identity, my positionality, and my role in reconciliation with Indigenous peoples in Canada and to decolonising and indigenising the academy through my research and teaching practices. It is an individual response to the Truth and Reconciliation Commission of Canada (TRC) calls to Action. I weave in personal narratives, theory, and poetry to engage with deep reflection on my lived experiences and the historical and social contexts that have influenced the construction of my identity and educational praxis. I examine these experiences within the context of colonisation, moving from historical to current perspectives and its specific implications within the Canadian context. Intersectionality and Indigenous theories and perspectives guide this examination. The aim is to further my understanding of Indigenous issues and to prepare myself to be an active and effective agent in the process of reconciliation with Indigenous peoples. The insights I have gained and share in this paper may inspire other educators to initiate their own journeys.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.053 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".