Informing the informal: visualizing laneway housing and increased density in Toronto
Bibliographic record
Abstract
Toronto is growing and attracting new population. Given that housing is a basic human need, Toronto’s population growth indicates a rising demand for housing. Meanwhile, spatial polarization of income is increasing in the city. Using Hulchanski’s illuminating study outlining those low and middle income households initially lived in the core of the city, near to transit networks and currently they cannot due to the high costs of housing this research investigates the physical and spatial capacity of a Toronto neighbourhood to increase affordable housing close to public transit while maintaining the physical character of the neighbourhood. As a means to address this affordable housing crisis laneway and informal housing is studied and the impact of these on the urban fabric, morphology, of neighbourhoods is studied. This research paper utilizes a mixed methods approach using semi-structured interviews, field research, spatial analysis and mapping, and the development of scenarios to test laneway and informal housing paradigms. This research concludes that: 1) informal housing and laneway housing can increase density while maintaining the physical character of a neighbourhood, 2) Toronto has an under-utilized laneway system that is a missed opportunity to increase density, 3) The current density limit for stable neighbourhoods defined by Toronto’s Zoning By-law is not realistic and there is a potential for increasing density limit while retaining the integrity of neighbourhood character, 4) Four to six storey laneway developments can create a new distinct character in laneways without changing street character.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".