Straddling the divide: mainstream populism and conservatism in Howard's Australia and Harper's Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper builds on the insights of Sawer and Laycock (2009) to explore similarities in the use of populist discourse by former Australian Prime John Howard and current Canadian Prime Minister Stephen Harper. While Sawer and Laycock label this discourse ‘market populism’ and focus on economic issues, here it is argued that Howard and Harper's populism is better understood as ‘mainstream populism’ due to the equal importance of sociocultural issues in their discourses. To demonstrate this, the treatment of issues such as immigration, multiculturalism, the culture wars, criminal justice, and childcare is considered. It is further suggested that such populist policies were used to satisfy rival wings of their respective parties – neoliberals and social conservatives – that do not always share the same priorities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it