Walking With Our Relatives: Co-Designing an Anishinaabe-Led Evaluation Approach
Bibliographic record
Abstract
This article shares stories about the development of the Gaa-giigishkaa- kaawasowaad “A Place Where Pregnant Women Gather” Clinic at Mewinzha Ondaadiziike Wiigaming and the Anishinaabe-led evaluation approach developed to support learning about the clinic’s journey. The clinic, located in northern Minnesota, focuses on maternal–child health integrative care, prioritizing Anishinaabe cultural values and practices. The inception of the clinic has been informed by community priorities, vision, and includes important protocols, such as visiting with Elders at the outset and offering asemaa (traditional tobacco), to guide its development. Alongside the story of the clinic, the authors share the development of an Anishinaabe-led evaluation approach that supports ongoing learning and wellness within the clinic. By reflecting on the clinic’s first 2 years of operation, the authors assess where they have come from and draw forward learnings gathered so far. These stories highlight the critical role of culturally rooted evaluation in supporting the health and wellness of American Indian families and transforming community experiences.
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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 | 0.089 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".