Seeing in Colour: A Black Housing Equity Framework to Address Anti-Black Racism in Housing and Homelessness
Bibliographic record
Abstract
The Black population in Canada is notably diverse, encompassing a broad spectrum of ethnicities, backgrounds, circumstances, and experiences. This doctoral study is dedicated to shedding light on the fundamental role that systemic anti-Black racism plays in fostering housing instability for Black Canadians, and aims to establish a framework for addressing anti-Black racism within the housing and homelessness sector. Acknowledging the influence of White supremacy and anti-Black racism, this research adopts Critical Race Theory (CRT) as the guiding theoretical framework. Employing a multifaceted methodology that integrates design science, Afrocentric, and autoethnographic research approaches, the study conducts thorough semi-structured interviews with eight Black individuals with lived and living experiences (BPWLE) in Calgary, along with nine Black key informants across Canada, to gain deeper insights into the impacts of systemic anti-Black racism. The results of the interviews with BPWLE underscore the link between systemic racism and housing insecurity, while the key informant interviews reveal the pervasive nature of anti-Black racism in the workforce, influencing policies and practices negatively. Research contributors collectively recognize the widespread existence of anti-Black racism across various sectors and the need for policies and practices to be rooted in equity and anti-oppression. The discourse underscores the importance of centering the perspectives of Black individuals and communities when shaping housing policies and practices. It emphasizes the inadequacy of a colour-blind, one-size-fits-all approach in eradicating systemic anti-Black racism and advocates for an intersectional perspective. Subsequently, a transformative Black Housing Equity Framework (BHEF) emerged from these interviews. This framework encapsulates guiding principles aligned with the values of Black communities alongside operational questions designed to guide policymakers, housing practitioners, and other partners in formulating equitable policies and practices. The BHEF represents a pivotal stride towards acknowledging the systemic anti-Black racism and discrimination confronted by Black communities in their endeavours to secure and maintain housing, offering a beacon of hope for a more equitable future.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.040 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".