The Polarization of Popular Culture: Tracing the Size, Shape, and Depth of the “Oil Spill”
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
Abstract Recent research suggests that political polarization has spilled over into otherwise mundane areas of social life. And yet, the size, shape, and depth of that spillage into popular culture are generally unknown. Relying on a sample of 135 widely known movies, TV shows, musicians, sports, and leisure activities, we investigate these issues. We find the “oil spill” of polarization into popular culture is large but loosely organized into multiple fairly shallow pools. Cultural polarization is also asymmetric. Liberals like a wide variety of popular culture, do not dislike conservative popular culture, and their tastes are more rooted in their sociodemographics. Conservatives, on the other hand, like a much narrower range of popular culture, dislike the culture created and liked by Black and urban liberals, and their tastes seem to be more directly rooted in their political ideology. Potential implications of an asymmetric culture war, and ideas for future research, are discussed.
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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 | 0.001 |
| Science and technology studies | 0.003 | 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 it