Self-Fulfilling Misperceptions of Public Polarization
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
Mass media convey deep divisions among citizens despite scant evidence for such ideological polarization. Do ordinary citizens perceive themselves to be more extreme and divided than they actually are? If so, what are the ramifications of such misperception? A representative sample from California provides evidence that voters from both sides of the state’s political divide perceive both their liberal and conservative peers’ positions as more extreme than they actually are, implying inaccurate beliefs about polarization. A second study again demonstrates this finding with an online sample and presents evidence that misperception of mass-level extremity can affect individuals’ own policy opinions. Experimental participants randomly assigned to learn the actual average policy-related predispositions of liberal and conservative Americans later report opinions that are 8–13% more moderate, on average. Thus, citizens appear to consider peers’ positions within public debate when forming their own opinions and adopt slightly more extreme positions as a consequence.
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.
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 | 0.002 | 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 | 0.000 |
| 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