Projection in Politicians' Perceptions of Public Opinion
Bibliographic record
Abstract
Research has shown that politicians' perceptions of public opinion are subject to social projection. When estimating the opinions of voters on a broad range of issues, politicians tend to assume that their own preferences are shared by voters. This article revisits this finding and adds to the literature in three ways. First, it makes a conceptual contribution by bringing together different approaches to the analysis of projection and its consequences. Second, relying on data from surveys with politicians ( n = 866) in four countries (Belgium, Canada, Germany, and Switzerland) conducted between March 2018 and September 2019, it shows that there is more projection in politicians' estimations of their partisan electorate than in their estimations of the general public or of their geographic district. Third, comparing the data on politician projection with data from parallel surveys with citizens, the article reveals that—at least in three out of the four countries studied here—elected politicians are not better at avoiding erroneous projection than ordinary citizens. The article discusses the implications of these findings for the workings of representative 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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".