Indigenous Perspectives in Program Evaluation: A scoping literature review exploring wise practices for program evaluation with Indigenous communities in northern Manitoba
Bibliographic record
Abstract
This study explored how organizations that offer programming and services in northern Indigenous communities could inform, adapt, and improve their evaluation approaches to involve an Indigenous perspective. Without this research, program evaluation may continue to be conducted within a Western perspective, a view that does not consider an Indigenous paradigm or cultural considerations. To examine Indigenous perspectives in program evaluation, the researcher conducted a scoping literature review using 15 secondary sources from Australia, Canada, and the United States of America published from 2010-2020. Through a decolonized methodology, the researcher sorted the data into themes according to the core values of an Indigenous Evaluation Framework. The findings contributed to the literature by addressing the gaps of decolonizing program evaluation, integrating cultural approaches, and instilling an Indigenous paradigm. Relevant to organizations that work with Indigenous communities, the research generated wise practices to engage program evaluation in a culturally appropriate manner. Building from this study, ongoing research is needed to support Indigenous perspectives in program evaluation.
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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 | 0.091 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.021 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".