Encounters with difference in the subdivided house: The case of secondary suites in Vancouver
Bibliographic record
Abstract
Policies that encourage tenure mix as a strategy to help narrow socio-spatial distance between homeowner households and their renter counterparts have a long and controversial history in North American and European cities. Research that seeks to evaluate the merits of such policies has typically focused on the frequency of encounters between these two types of household, at the expense of the quality of this contact. Accessory apartments in subdivided houses (also known as secondary suites) provide a germane micro-scale environment to examine the content of interactions between homeowners and renters. Inspired by Gill Valentine’s work on ‘encounters with difference’ and using a series of interviews with secondary-suite homeowner-landlords and their tenants in the city of Vancouver, this article illustrates three types of encounters across tenure-based difference. These examples of conflictive, tolerant, and respectful encounter provide helpful material to reflect on the limitations of tenure mix as a macro-scale policy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.043 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 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".