Reflections on Being a Learner: The Value of Relationship-based Community Evaluations in Indigenous Communities
Bibliographic record
Abstract
Abstract: Drawing on Donna M. Mertens and Amy T. Willson’s work on transformative paradigms in program evaluations, together with the author’s experience working in partnership with First Nations communities in Ontario, this paper explores the lessons learned from the process of moving between assumptions and application using the transformative paradigm in First Nations evaluations; explores the relationships between power, discourse, and paradigms in the relationship between Western and Indigenous ways of knowing and being; and asks what steps an can evaluator take to ensure that local epistemological and ontological perspectives are respected and captured.
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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 | 0.097 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.053 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".