Housing Vancouver, 1972–2017: A personal urban geography and a professional response
Bibliographic record
Abstract
The forum includes a research paper, preceded by a brief introduction and followed by five short responses from Pablo Mendez, Loretta Lees, Margaret Walton‐Roberts, Ilse Helbrecht, and Alison Mountz. Mountz's introduction sets the context for the paper and makes some framing remarks on David Ley's career. The main paper examines the housing question in Vancouver, in the period from 1972 to 2017. Re‐examining a number of Ley's research projects over this period, three broader themes are explored: the continuity of the housing crisis, and its reconfiguration over the period under study; the contrast between innovative and interventionist housing policy in the 1970s, with the later withdrawal of the state from significant intervention while endorsing market solutions; and the new centrality of housing as an empirical and analytical category in current human geography. This period saw upscaling from the 1970s welfare state to neoliberal globalization, including wealth immigration and off‐shore property investment that accelerated serious metropolitan affordability problems. Following this research paper, colleagues and former students respond to the paper and locate the contributions in David Ley's broader career. Their commentaries address Ley's key contributions to debates in human geography, including his work on gentrification, urbanism, urban activism, global migration, art, aesthetics, and ethnography.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".