Replication Data for: The Distance Between Us: The Role of Ideological Proximity in Shaping Perceptions of Inter-Partisan Relationships
Bibliographic record
Abstract
Escalating hostility between partisans threatens democratic governance and social cohesion by eroding trust and fuelling discriminatory behaviour towards opposing groups. This study delves into how people perceive the relations between different partisan groups and why certain pairs of partisans are viewed as friendlier or more hostile toward one another. Drawing on similarity-attraction theory in social psychology and affective polarization research, I argue that citizens perceive the relationship as more friendly between individuals who support ideologically similar parties. The claim is tested and empirically supported by using a novel survey item, which asks about the likelihood of two partisans becoming good friends, in three multiparty democracies: Canada, Germany, and the UK. The findings suggest that parties’ ideological proximity not only shapes citizens’ perceptions of parties themselves but also influences their views of fellow citizens across party lines. By demonstrating that people consider party proximity and ideological alignment when gauging inter-partisan relations, the study sheds light on how ideological and affective dimensions intertwine within these relationships in multiparty democracies.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.131 | 0.112 |
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".