Neoliberal Populism in Ontario: Premier Doug Ford’s Strategic Politics
Bibliographic record
Abstract
The 2018 election of Premier Doug Ford and the Progressive Conservative (PC) government ushered in a new era of neoliberal populism in Ontario, Canada. Ford’s election platform, titled a “Plan for the People,” resonated with the business elite who supported his free-market reforms but also with middle-class and blue-collar workers living in suburban and northern areas of the province. The article examines how Ford positioned his rivals as “out of touch” members of the political and cultural urban elite, responsible for a spiralling deficit that would economi-cally burden hard-working people. Unlike many other right-wing populist leaders, who have relied on xenophobic or anti-immigrant narratives, we argue that Ford’s populist stance is dema-gogic and pragmatic. This enabled him to pivot and shift his political strategy to amass support from a diverse range of economic, racial, ethnic, and religious groups, including new immigrants. We draw on newspaper articles, public documents and reports, as well as thirteen interviews with politicians, teachers and civil servants. The article highlights how Ford’s government operated to weaken democratic institutions through measures such as “strong mayor powers,” invoking the notwithstanding clause, as well as undermining the public sector. We trace how Ford’s populism undermined public education through overt and subtle measures that weaken school boards and unions while advancing privatization. We show how Ford bypassed intermediaries, in this case, school boards and teachers’ unions, and appealed directly to “the parents” through the media and employed cli-entelist strategies such as cash transfers under the guise of “parental choice” to hollow out public education. The analysis demonstrates how Ontario stands out as a unique case study for exam-ining neoliberal populism in Canada and North America.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.041 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".