Selective Avoidance on Social Media: A Comparative Study of Western Democracies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the phenomena of political unfriending and content removal on social media in three Western democracies—France, the United Kingdom, and the United States. We seek to understand the role of crosscutting discussion, confrontational discussion style, and ideological extremity in triggering unfriending and content removal on social media, while shedding light on cross-country differences. The findings show that selective avoidance behaviors are much more common in the United States than either in France or the United Kingdom. They also show that crosscutting discussion and confrontational style are the predictors of selective avoidance across all the above countries, while ideological extremity plays a role in the United States only. We suggest that while social media provide opportunities for citizens to engage in discussions with people with dissimilar political views and socioeconomic backgrounds, they also allow them to easily reestablish more homophilous environments via content removal and tie dissolution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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