Affective polarization and institutional confidence in Canada
Bibliographic record
Abstract
Confidence in political institutions has reportedly been in decline over the past 40 years. Yet there is heterogeneity in how this phenomenon has manifested across countries, political institutions and people with different partisan commitments. The increasing antagonism towards opposition partisans – known as affective polarization – may hasten this decline, undermining types of institutional confidence that were perceived to be more durable. This article investigates the effects of affective polarization across non-partisan institutions in Canada. We contend that stronger levels of affective polarization that produce lower levels of trust in partisan institutions may spill over to other non-partisan institutions because polarized individuals may perceive all institutions as reflecting government priorities. Using data from the 2004–2021 Canada Election Studies, we find evidence that spillover is happening to some degree, but that these effects are driven by specific party dynamics and government/opposition status. Although those who support the opposition party report less confidence in non-partisan institutions than government supporters across both main parties, Conservatives who are affectively polarized have lower institutional trust overall, regardless of whether their party is in government or opposition.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".