Exploring the relationship between housing conditions and Métis Nation of Ontario citizen’s health: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Housing is an important social determinant of health as the lack of housing or substandard housing conditions can negatively impact people's health and wellbeing. Indigenous Peoples in Canada are three times more likely to live in substandard housing than non-Indigenous people. The objective of this study is to examine the thoughts, feelings, and stories of citizens of the Métis Nation of Ontario (MNO) on how their housing conditions impact their health. METHODS: Thirty-five (35) MNO citizens were recruited for the study, and seven focus groups were conducted between August 2022 and February 2023. All focus groups were conducted via Zoom with 3-9 participants, one facilitator, one note-taker, and one MNO Senator. All focus groups were recorded. Each transcript was coded and analyzed using thematic analysis by two independent coders. RESULTS: Seven themes were derived from all focus groups: housing needs and conditions, affordability of shelter costs, renting, infrastructure and connectedness, impacts of housing on mental and emotional health, impacts of housing on physical health, and improvements to housing programs and supports. CONCLUSIONS: This is the first Métis-specific study to explore and gather the lived experiences and stories of MNO citizens regarding the impact of housing conditions on their health. Our findings revealed a multifaceted relationship between housing and health, extending beyond individual's living conditions, with a significant impact on Métis citizens' mental health. The results will be used to inform MNO housing programs to increase Métis homeownership and improve affordable housing options.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".