Bibliographic record
Abstract
Abstract This chapter examines the impact of macroeconomic, political, and fiscal policy variables on the Canadian federal government’s popularity from 1978 to 2018. It observes a decline in the impact of the macroeconomic variables over time. This decline coincides with a shift in the government’s fiscal policy agenda which has been centred on austerity and deficit reduction since the early 1990s. Until then, Canadians preferred budget deficits and the effect of the economy on executive approval was clear and consistent. As deficits became unsustainable during the economic crisis of the early 1990s, balancing the budget became the government’s main objective. The government’s austerity discourse and actions convinced many Canadians of the purported benefits of a balanced federal budget. Since then, Canadians have rewarded the government for a reduction of budget deficits, and the impact of the economy on the government’s popularity became inconsistent. The authors demonstrate this over-time change using Wald tests, split samples, and rolling regressions. In that respect, their findings provide support to one of the theoretical perspectives laid out in this volume’s introduction, according to which the salience of economic issues has changed over time, a factor that partly explains the variation observed in the relationship between economics and executive approval.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".