Why Don’t We Do Something? The Societal Problematization of “Homelessness” and the Relationship between Discursive Framing and Social Change
Bibliographic record
Abstract
Despite decades of public support for ending homelessness, there is little evidence that homelessness has decreased in Canada. Instead, Canadian communities continue to respond to rising numbers of people without homes through emergency response measures that do little to prevent or end the problem. In sharp contrast, research has documented that homelessness is not inevitable and can be addressed with relatively insignificant government financing. Canada has the ability to end this problem. The question is: why don’t we? This study explores Canada’s political response to this issue by tracing the social construction of “homelessness” since its emergence in the 1980s. Drawing on social problem theory, this interpretive study uses a grounded theory approach to explore the construction of this problem by homelessness advocates and the Canadian media. Triangulating this data with social policy and key events, this study proposes a stage model to explain the “career” of this social problem. This research constitutes the first comprehensive study of the development of homelessness as a social problem in Canada. Results of the study suggest that homelessness has progressed through six stages in Canada and currently stands at a crossroads between institutionalization and transformation. Over the history of this problem, understandings of this issue have shifted from an emergency/disaster framework to an economic, bureaucratic, and scientific framework. Shifts in homelessness advocacy have been crucial to this transformation and are reflected in the development of two distinct “waves” of homelessness advocacy over the course of this problem’s history. This study argues that the differences between these waves are structurally produced through each wave’s divergent class-based experiences of early twenty-first century social and political changes. This study also offers the largest historical analysis of Canadian newspapers’ coverage of homelessness to date. Analysis revealed that newspaper coverage peaked in 1999 and has since declined. Findings suggest that Canadian reporters have frequently depoliticized and individualized this issue in class-based ways, while often failing to elucidate the connections between homelessness and Canada’s economic and social policies. This thesis concludes with an analysis of the contributions of this study to social problem studies, homelessness research, and social work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".