What explains elite affective polarization? Evidence from Canadian politicians
Bibliographic record
Abstract
Abstract Concerns about affective polarization are on the rise globally, and it has been associated with negative outcomes such as diminished trust in government and discrimination against out‐partisans. While elected politicians are typically thought to be a major source of mass‐level affective polarization, and despite the policy and representation consequences of heightened partisan hostility in legislatures, existing research has focused almost exclusively on the measurement and explanation of affective polarization among citizens. As a result, we know far less about the magnitude and sources of elite affective polarization. Here, we take a step towards addressing this gap using an original survey of hundreds of Canadian local politicians, a setting uniquely situated for addressing the role of a host of individual‐level and institutional‐level predictors of affective polarization. We find that Canadian local politicians are, on average, less affectively polarized than the citizens they represent. However, levels of affective polarization among these politicians vary considerably, with higher levels of affective polarization among politicians who are ideologues, partisans, and who harbor strong progressive ambition. We conclude by discussing the implications of our findings for research on affective polarization and describe the need for comparative studies of affective polarization among political elites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".