The People’s Champ: Doug Ford and Neoliberal Right-Wing Populism in the 2018 Ontario Provincial Election
Bibliographic record
Abstract
The 2018 Ontario provincial election marked a decisive shift in the political direction of Canada’s most populous province. The election brought an end to the long reign of the Ontario Liberal Party (2003–2018), whose government devolved into a series of scandals that resulted in a third-place finish. The Liberal’s defeat came at the hands of the Progressive Conservative Party led by former Toronto city councillor, Doug Ford. The Progressive Conservative’s victory was propelled on the back of Ford’s deeply populist campaign where he promised to reassert the interests of ‘the people,’ expel the influence of elites and special interests, and clean up government corruption. This campaign discourse led many political opponents and media pundits to accuse Ford of importing the nativist, xenophobic, and divisive rhetoric of other radical right-wing populist leaders. This article advances the argument that rather than representing the importation of ‘Trumpism’ or other types of radical right-wing populism, Ford’s campaign is better understood within the tradition of Canadian populism defined by an overarching ideological commitment to neoliberalism. In appealing to voters, Ford avoided the nativist and xenophobic rhetoric of populist leaders in the United States and Western Europe, offering a conception of ‘the people’ using an economic and anti-cosmopolitan discourse centred upon middle class taxpayers. This article makes a contribution to both the literatures on Canadian elections and populism, demonstrating the lineage of Ford’s ideological commitment to populism within recent Canadian electoral history, as well as Ford’s place within the international genealogy of right-wing populism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".