The Creatures of the Province Doctrine and the Neoliberalization and De-Democratization of Local Governance in Toronto from 1996-2023
Bibliographic record
Abstract
In 2022, Ontario Premier Doug Ford announced new legislation, the Strong Mayors, Building Homes Act. The Act enshrined something once unthinkable to people living in the City of Toronto: granting the mayor the power to veto decisions made by the City Council while requiring the council to summon a super-majority (two-thirds) of votes to overrule the mayor. Any new local bylaw passed seen as clashing with “provincial priorities” could be vetoed by the mayor, creating a direct political link on all local issues between the municipal mayor’s and provincial government premier’s offices. This dissertation questions broad assumptions about, and examines and theorizes to what degree, this type of governing was a stark break from, or a continuation of, the longstanding norms pertaining to liberal democratic institutions and intergovernmental governance between the Government of Ontario and the City of Toronto. Using three case studies over the period from 1996 to 2023, the dissertation focuses on three Ontario premiers: Mike Harris (1996-2002), Dalton McGuinty (2003-2006), and Doug Ford (2018-2023). The argument put forth is that in the neoliberal era, the provincial government has routinely utilized the creatures of the province doctrine to restructure liberal democratic institutions and undercut democratic decision-making processes within the City of Toronto. This was done in the name of the neoliberalized notion of “efficiency” through centralizing power and insulating neoliberal austerity measures from critique.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".