Conducting Participatory Action Research with Canadian Indigenous Communities: A Methodological Reflection
Bibliographic record
Abstract
A central challenge with participatory action research (PAR) pertains to discrepancies between principles and practice. What sounds simple in theory (e.g., establishing a respectful collaboration) is often much more complex in real community settings. The challenges, lessons learned, and successes of PAR were examined within the context of a large national research project that involved 8 First Nation communities and academics. To engage in the process of reflective examination, two methodological approaches were utilized: (1) a qualitative interview study with 19 project members about their experiences within the project, and (2) a secondary qualitative analysis of the author’s own experiences and observations (as recorded in research journals). This paper summarizes some of the barriers to conducting PAR with Indigenous communities (i.e., themes of distrust/personal safety concerns, community readiness, waning motivation, financial stress, power differences, and differing norms/expectations) , as well as some of the lessons that were learned about how to overcome these challenges and cultivate strong, healthy research relationships.
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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 | 0.041 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.049 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".