Bibliographic record
Abstract
Despite decades of efforts to combat homelessness, many people continue to experience it in Canada’s major cities. There are a number of barriers that prevent effective responses to homelessness, including a lack of agreement on the fundamental question: what is homelessness? In Multiple Barriers, Alison Smith explores the forces that shape intergovernmental and multilevel governance dynamics to help better understand why, despite the best efforts of community and advocacy groups, homelessness remains as persistent as ever. Drawing on nearly 100 interviews with key actors in Vancouver, Calgary, Toronto, and Montreal, as well as extensive participant observation, Smith argues that institutional differences across cities interact with ideas regarding homelessness to contribute to very different models of governance. Multiple Barriers shows that the genuine involvement of locally based service providers, with the development of policy, are necessary for an effective, equitable, and enduring solution to the homelessness crisis in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.010 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.457 | 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".