The asymmetrical structure of left/right disagreement
Why this work is in the frame
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Bibliographic record
Abstract
The left/right semantic is used widely to describe the patterns of party competition in democratic countries. This article examines the patterns of party policy in Anglo-American and Western European countries on three dimensions of left/right disagreement: wealth redistribution, social morality and immigration. The central questions are whether, and why, parties with left-wing or right-wing positions on the economy systematically adopt left-wing or right-wing positions on immigration and social morality. The central argument is that left/right disagreement is asymmetrical: leftists and rightists derive from different sources, and thus structure in different ways, their opinions about policy. Drawing on evidence from Benoit and Laver’s (2006) survey of experts about the policy positions of political parties, the results of the empirical analysis indicate that party policy on the economic, social and immigration dimensions are bound together by parties on the left, but not by parties on the right. The article concludes with an outline of the potential implications of left/right asymmetry for unified theories of party competition.
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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 | 0.000 | 0.000 |
| 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