Housing affordability, market interventions, and policy platforms in the 2022 Ontario provincial election
Bibliographic record
Abstract
Abstract Since the Great Recession, many cities around the world have undergone extreme demographic changes as people and capital resettle into urban areas. This has resulted in issues of gentrification and displacement forcing many governments to address growing concerns of housing insecurity. Housing policy is a function of political ideologies and social conditions drawing from market‐based housing supply (MBHS) solutions or demand‐side interventions (DSI) to alleviate housing cost burdens. Yet, debates on their effectiveness have often undermined their ability to grow to scale leaving many households in precarious housing situations. This paper focuses on the 2022 Ontario provincial election to uncover how Canadian political parties frame housing insecurity and their policy platforms. This paper finds all political parties promote the MBHS framework, yet various degrees of the DSI framework. Embedded within this variation are questions of federalism with responsibility shifting between provincial and municipal governments. The findings reveal while different forms of neoliberal ideology inform the policy platforms of political parties, federalism plays a significant role in framing the level and scale of government involvement.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".