Neither a Trait nor Wildly Fluctuating: On the Stability of Populist Attitudes and its Implications for Empirical Research
Bibliographic record
Abstract
Abstract The literature on populist attitudes frequently makes one of two assumptions: populist attitudes are either stable or unstable. However, few studies have examined these diverging assumptions empirically. We use panel data collected over six panel waves between 2017 and 2021 in Germany to assess the stability of populist attitudes. Integrating inter-individual stability (variable-centred) and intra-individual stability (individual trajectories), we find that populist attitudes are neither fully stable (trait) nor fully flexible (state). For example, some respondents constantly changed their view on populism while the attitudes in one out of three individuals remained stable. We also explore empirical consequences and find that populist attitudes are more closely linked to vote choice when they are stable. Accordingly, we argue for a more nuanced understanding of the dynamics of populist attitudes, both at the variable and individual levels, where these attitudes are stable and consequential for only a subset of individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".