Outsiders Within: Claiming Discursive Space at National Homelessness Conferences in Canada
Bibliographic record
Abstract
Homelessness in Canada is a large and growing problem affecting more than 235,000 men, women, youth, and families per year, in urban, suburban, rural and Northern communities. Though it is produced by economic and policy drivers including colonization, income insecurity, and state withdrawal from housing provision, policies on homelessness tend to focus on service provision rather than addressing root causes. This article reviews activist, advocacy, service and policy responses to homelessness in Canada, and in particular, homeless sector conferences. Taking as its starting-point a demonstration at a 2014 national conference on homelessness, it examines these conferences as important sites of governance in which service organizations collaborate in the development and delivery of policy. Conferences’ normative culture, and their discursive construction of homelessness as a technical problem, tend to leave unchallenged the prevailing economic, social, political and institutional arrangements that produce homelessness. Recent interventions by people facing homelessness and their allies, though, have claimed discursive space at national homelessness conferences for outsider perspectives and demands. These interventions open possibilities for new alliances, analyses, and tactics that are necessary for ending homelessness.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.058 | 0.023 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".