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 Public opinion research has shown that voters accept many falsehoods about politics. This observation is widely considered troubling for democracy – and especially participatory ideals of democracy. I argue that this influential narrative is nevertheless flawed because it misunderstands the nature of political understanding. Drawing on philosophical examinations of scientific modelling, I demonstrate that accepting falsehoods within one's model of political reality is compatible with – and indeed can positively enhance – one's understanding of that reality. Thus, the observation that voters accept many political falsehoods does not necessarily establish that they lack political understanding. I then address three worries: that voters cannot generally engage in such political modelling; that political modelling obscures facts that are crucial to political understanding; and that successful political modelling would require knowing that one's model contains falsehoods. My responses reveal how, going forward, we should measure political ignorance, and they highlight the standing importance of participatory democracy.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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