The Cedar Project: Racism and its impacts on health and wellbeing among young Indigenous people who use drugs in Prince George and Vancouver, BC
Bibliographic record
Abstract
Racism continues to drive health disparities between Indigenous and non-Indigenous peoples in Canada. This study focuses on racism experienced by young Indigenous people who have used drugs in British Columbia (BC), and predictors of interpersonal racism. Cedar Project is a community-governed cohort study involving young Indigenous people who use drugs in Vancouver and Prince George, BC. This cross-sectional study included data collected between August 2015-October 2016. The Measure of Indigenous Racism Experiences (MIRE) scale was used to assess experiences of interpersonal racism across 9 unique settings on a 5-point Likert scale, collapsing responses into three categories (none/low/high). Multinomial logistic regression models were used to examine associations between key variables and interpersonal racism. Among 321 participants, 79% (n = 255) experienced racism in at least one setting. Thirty two percent (n = 102) experienced high interpersonal racism from police, governmental agencies (child 'welfare', health personnel), and in public settings. Ever having a child apprehended (AOR:2.76, 95%CI:1.14-6.65), probable post-traumatic stress (AOR:2.64; 95%CI:1.08-6.46), trying to quit substances (AOR:3.69; 95%CI:1.04-13.06), leaving emergency room without receiving treatment (AOR:3.05; 95%CI:1.22-7.64), and having a traditional language spoken at home while growing up (AOR:2.86; 95%CI:1.90-6.90) were associated with high interpersonal racism. Among women, experiencing high interpersonal racism was more likely if they lived in Prince George (AOR:3.94; 95%CI:1.07-14.50), ever had a child apprehended (AOR:5.09; 95%CI:1.50-17.30), and had probable post-traumatic stress (AOR:5.21; 95%CI:1.43-18.95). Addressing racism experienced by Indigenous peoples requires immediate structural systemic, and interpersonal anti-racist reforms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".