Kwayâtisiwin (“We Prepare”): Understanding the Methods of Preparation for Evaluating Nêhiyawak-based Research
Bibliographic record
Abstract
The evaluation of Indigenous research practices overlooks the cultural protocols, traditions, and ceremonies that are critical to conducting research with Indigenous communities. To illustrate, the authors share how practices of Kwayâtisiwin (defined as “We Prepare” in the Nêhiyawêwin, Plains Cree language) attune people’s minds, bodies, and intentions to the Nêhiyawak (Plains Cree) tradition well before formally recognized research begins. This is not a how-to guide on how to engage with Nêhiyawak communities; instead, it is a way to show the invisible labour that is overlooked in academic evaluations of what is successful and meaningful research. In particular, the authors identify three methods of Kwayâtisiwin through their work in serving Nêhiyawak communities within Central Alberta. They share ontological and philosophical insights to challenge what constitutes “impact” and “real research” for the betterment of the Northern Door and the generations that follow in academia.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.053 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".