HOUSING AS A HUMAN RIGHT: UNDERSTANDING THE NEED TO ALIGN TORONTO'S LEGAL PLANNING FRAMEWORK WITH CITY COUNCIL'S VISION TO END HOMELESSNESS & THE AFFORDABLE HOUSING CRISIS
Bibliographic record
Abstract
While international law defines housing as a basic human right, many Torontonians are being denied access to secure, adequate and affordable housing. The primary objective of this article is to examine the interplay between city policy statements on ending homelessness through the maintenance and creation of affordable housing stock, and the legal mechanisms required to execute these policies. This article will begin with an examination of the goals of the Streets to Homes program implemented in 2005 and the most recent policy recommendations outlined in the 2008 report from city council entitled, Housing Opportunities Toronto: A framework for affordable housing. Following a brief introduction to these two government initiatives, it will be determined whether the existing legal planning framework coincides with the Toronto City Council’s vision to end the homelessness and affordable housing crisis by 2018. The legal mechanisms examined in this paper will include the Municipal Shelter by-law (2003), Section 37 of Ontario’s Planning Act, and the need to implement inclusionary zoning to facilitate the ability of the city and developers to respond to the homelessness crises in the long-term. When combined, these legal tools have the ability to support the creation of new, secure, adequate and affordable housing stock in the City of Toronto in both short- and long- term.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.043 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".