Indigenizing : one heart at a time
Bibliographic record
Abstract
Indigenizing the academy, while complicated, fluid, and diverse in its pursuits, is underway in most if not all post-secondary institutes in Canada. This has forced many people working in these institutions to Indigenize. But what has remained unclear is how one sets about to Indigenize themselves and their practice. Using Indigenous Storywork (Archibald, 2008) this project examines written stories by 11 non-Indigenous post-secondary educators in Stó:lō Téméxw (territory) told from their positions as non-teaching staff, professors, and administrators. Their stories tell how they shifted their practice to include Indigenous content and pedagogies, and honour Indigenous ways of knowing and being. They also share insights about becoming an Indigenizer. The Stó:lō researcher uses Indigenous Storywork as theory with an emphasis on Stó:lō teachings. The principles of Indigenous Storywork guide the methods for the research and the meaning making process. Referred to as Storywork Listening, the written stories are visited again and again with each revolution making meaning and understanding differently within an Indigenous paradigm. The stories elucidate six themes on the path to Indigenizing: We Were Children; Historical Amnesia; Decolonization; Coming to Know; Ceremony as Teacher; and Learning from Indigenous Peoples. These themes are brought together into a metaphorical river contributing to Indigenizing the Academy. The complexities of Storywork Listening educate one’s heart, mind, body and spirit wherein the power of story is experienced as a new story unfolds with a promise for the future. A future of Indigenizing will be built with a deep knowledge of the historic past and its effect on today; on good Indigenous/non-Indigenous relationships; respect for ways of knowing other than our own; and, with changes in how we view and act in the world we share. It will be hard work, and it will take the efforts of many, but it will be accomplished one heart at a time.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.025 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".