Bibliographic record
Abstract
Abstract This article introduces the miyo‐wîcêhtowin Hiring Framework , an Indigenous‐led, values‐based model developed to transform public sector hiring practices. Grounded in Cree teachings of “building good relations,” the framework emerged from a mixed‐methods analysis of over 1,500 municipal job descriptions from the City of Saskatoon. The study uncovered systemic bias across categories such as age, race, ability, language, and education, revealing how hiring language can exclude Indigenous peoples and other equity‐deserving groups. Drawing on Critical Race Theory, intersectionality, discourse analysis, and human rights frameworks, the research repositions hiring as a relational and governance act—not a neutral HR function. The miyo‐wîcêhtowin Hiring Framework offers practical tools and cultural principles to reimagine hiring systems grounded in respect, reciprocity, and Indigenous resurgence. It calls on public institutions to move beyond symbolic REDI commitments toward structural change by embedding Indigenous worldviews and leadership into recruitment processes, advancing equity and self‐determination in Canadian public administration.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 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".