Systems of Inequity: Representations of Immigrants, Refugees, and Newcomers in Canada's National Housing Strategy
Bibliographic record
Abstract
Housing insecurity and homelessness in Canada have significant implications in the lived experiences of people. It is estimated that on any given night in Canada, approximately 35,000 people experience homelessness; further, estimates of 235,000 people experience homelessness in a given year (Gaetz, Dej, Richter & Redman, 2016). In addition, it has been estimated that 1.5 million people in Canada do not meet stable housing requirements. These estimates of housing insecurity and homelessness are impacted by myriad factors including economics, accessibility, politics, race and historical implications; conversely, housing directly influences many other social determinants including, health, access to services and social inclusion. Research has demonstrated that immigrants, refugees, and newcomers to Canada often find themselves in precarious housing circumstances. This precarity is magnified for a variety of reasons such as immigration status, access to social services, employment security, and discrimination. Another factor, which directly influences housing security and homelessness are current political climates. In this case, the most recent federal government promised and delivered on commitments to establish a National Housing Strategy (NHS). The purpose of housing strategies are to provide plans, goals, and financial commitments to addressing housing issues. Because housing is embedded in larger contextual milieus, it is critical to examine how individuals and circumstances are addressed in federal policies such as the National Housing Strategy (NHS). Research that addresses the complex experiences of immigrants, refugees, and newcomers can help to create policies that are inclusive. The purpose of this research was to examine how Canada’s National Housing Strategy reflected the unique housing needs of immigrants, refugees, and newcomers. The research question was answered using a version of intersectionality-based critical policy analysis (IBCPA) developed by Hankivsky et al. (2012); data collection and analysis was divided into two data sets and two phases. The first stage of analysis and data set focussed on the NHS document specifically. Using a set of critical questions outlined by the method, the NHS was examined, revealing three main themes related to immigrants, refugees, and newcomers: problematic representations, conceptualizations of power, and how context impacts housing for immigrants, refugees, and newcomers. Using intersectionality as the theoretical perspective, these themes are discussed in relation to each other and current hegemonic ideologies in Canadian society. The second phase of the research uses the second data set: interview data I collected from four policy stakeholders. In this phase, I presented interview participants with the results from the first phase of the project. Using semi-structured interviews, I explored with them the history of housing policy in Canada, how the current NHS was generally received, and how they thought it would impact immigrants, refugees, and newcomers given housing precarity in a segment of this population. Again, using intersectionality to frame the results, four themes emerged: the absence of lived experiences related to housing insecurity and homelessness among immigrants, refugees, and newcomers, the impact policies have on housing issues, overall neo-colonial and racist representations of immigrants, refugees, and newcomers in the NHS, and solutions to the problem of housing insecurity and homelessness among immigrants, refugees, and newcomers. These results are discussed in relation to each other. Further, they assist in identifying and challenging power differentials to examine hegemonic ideologies which emerged in the data. In addition to the results from the research study, this dissertation explores several other areas of inquiry. One of the chapters explores my positionality as a researcher and how this positionality relates to research projects, while taking a critical and personal examination about how I am connected to this work. Another area of exploration is to describe the methodological processes and implications of using intersectionality-based critical policy analysis. Finally, I present a discussion paper in which the implications of using intersectionality as a theoretical proposition in nursing can be used to foster leadership for nurses aiming to impact social policy issues.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.035 | 0.014 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| 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".