Racially-motivated housing discrimination experienced by Indigenous postsecondary students in Canada: impacts on PTSD symptomology and perceptions of university stress
Bibliographic record
Abstract
OBJECTIVES: To examine the impacts of housing discrimination experienced by Indigenous postsecondary students on post-traumatic stress disorder (PTSD) symptomology and perceptions of university stress. STUDY DESIGN: Cross-sectional study. METHODS: Data were gathered via in-person surveys completed by 142 Indigenous students between 2015 and 2017. Associations were analyzed using phi coefficients and linear regression models adjusted for confounders. Qualitative data were examined using thematic analyses. RESULTS: Indigenous students who had children (almost 50% of the sample), were living with a romantic partner, and/or were between the ages of 25-44 years experienced significantly more racially-motivated housing discrimination than other Indigenous students in the sample. The frequency of housing discrimination in the past 12 months was significantly associated with increased PTSD symptoms; particularly, intrusive recollection and more perceived stress at university in linear regression models adjusted for confounders. Every 1-point increase in the frequency of housing discrimination on a 4-point scale resulted in a 5.4-point increase in PTSD score. Although living with a romantic partner resulted in more housing discrimination, it also served as a resilience factor, buffering the impact of housing discrimination on PTSD symptomology. Qualitative data indicated students faced Racially-motivated housing discrimination that was blunt and deliberate and highlighted the resourceful ways students sought to resist it. CONCLUSIONS: Racially-motivated housing discrimination exacerbated PTSD symptomology among Indigenous students and adversely impacted perceptions of their university experience. Efforts are needed to address housing discrimination directly, as well as provide greater family-focused housing and mental wellness supports to Indigenous students to reduce potential impacts of this public health problem on postsecondary success and degree completion.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".