Who said or what said? Estimating ideological bias in views among economists
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 There exists a long-standing debate about the influence of ideology in economics. Surprisingly, however, there are very few studies that provide systematic empirical evidence on this critical issue. Using an online randomised controlled experiment involving 2,425 economists in 19 countries, we examine the effect of ideological bias among economists. Participants were asked to evaluate statements from prominent economists on different topics, while source attribution for each statement was randomised without participants’ knowledge. For each statement, participants either received a mainstream source, an ideologically different less-/non-mainstream source, or no source. We find that changing source attributions from mainstream to less-/non-mainstream, or removing them, significantly reduces economists’ reported agreement with statements. This contradicts the image economists have/report of themselves, with 82% of participants reporting that in evaluating a statement one should only pay attention to its content. Our analysis provides clear evidence for the existence of ideological bias as well as of authority bias among economists. We also find significant heterogeneity in our results by gender, country, PhD completion country, research area and undergraduate major, with patterns consistent with the existence of ideological bias.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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