Cedar Project: Conducting Health Research with Indigenous Peoples in a Good Way
Bibliographic record
Abstract
The Cedar Project is an interdisciplinary, community-driven research project responding to the crises of HIV and Hepatitis C infection and contributing to the healing of young Indigenous people who use or have used drugs. We are a collective membership of Indigenous Elders, health/social service experts, researchers, and non-Indigenous allies. We situate our work in the context of strength, resilience, and rights to self-determination for Indigenous peoples while also acknowledging the ongoing impacts of historical, intergenerational, and current trauma, specifically those related to the child welfare systems. We provide epidemiological and qualitative evidence that reflects Indigenous perspectives of health and wellness. In this paper, we highlight over seventeen years of shared learnings on conducting research with Indigenous communities in a good way. Specifically, we elaborate on four key components of our unique project. First, our paradigm is to build on young Indigenous people's strengths while acknowledging grief and historical trauma. We recognize that Cedar participants are not statistics—they are relatives of Indigenous partners governing this study. Second, our processes are determined by Indigenous governance, led by Elders and rooted in cultural safety. Third, our research ethics are determined by terms of reference created by the Cedar Project Partnership and by embracing guidelines of TCPS and community-based research. Fourth, we are informed by multiple perspectives and research relationships between Elders, partners, students, academics, and research staff. Sharing our learnings with the larger research community can contribute to decolonizing research spaces by centering Indigenous knowledges and privileging Indigenous voice.
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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 | 0.125 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.005 | 0.010 |
| 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".