The Cedar Project : exploring resiliency and housing among young Indigenous peoples who use drugs during COVID-19 in two Canadian cities
Bibliographic record
Abstract
Background: Indigenous peoples have been resistant and resilient against the historical and ongoing colonial processes. Yet, young Indigenous peoples who use drugs are currently facing another challenge to their resilience in the form of the quadruple crises: overdose, racism, housing, and COVID-19. There is a lack of information on how aspects of the lives of young urban Indigenous peoples who use drugs have been impacted by COVID-19. The decampments on the downtown eastside of Vancouver, and punitive by-law policies of Prince George associated with COVID-19 responses have also necessitated an investigation of housing transience during the pandemic. Objective: This thesis evaluates how young Indigenous peoples who use drugs in two Canadian cities were impacted by COVID-19, with a focus on resilience and strengths. Specifically, it examines how resilience was supported during COVID-19, and how recent policy decisions have impacted the housing landscape. Methods: The Cedar Project is a prospective cohort study that involves young Indigenous peoples who use drugs in Vancouver and Prince George, BC. Baseline and nested COVID-19 cohort data from the Cedar Project were used in analyses. The nested COVID-19 study was conducted from February 2021-August 2022; and resilience was captured by the Connor-Davidson Resilience Scale (CD-RISC). Multivariable linear regression was conducted to investigate factors associated with resilience stratified by gender. Multivariable logistic regression was used to model housing transience in Prince George. Results: Among women, cultural and emotional connection and knowing “who you are” were significantly associated with higher resilience. For men privacy in housing was found to be associated with higher resilience. Ever having been incarcerated and ever having participated in sex work greatly increased the odds of having experienced housing transience during COVID-19, while high CD-RISC scores were protective – reducing the odds of experiencing housing transience. Conclusions: Our findings support the call for housing to be grounded in Indigenous culture and knowledges while further supporting what Indigenous peoples have known all along, culture, community, and Nation is where strength and resilience is found.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".