Bibliographic record
Abstract
Abstract A populist backlash has seized a number of Western democracies. Two broad sets of explanations have emerged to address the sources of this backlash, with credible empirical evidence for each. The first focuses on economic drivers, and specifically on global economic integration, and exposure to trade competition. The second turns instead to cultural explanations, arguing that the shifting political winds are due to strictly nonmaterial considerations, like status threat and racial beliefs. How might we reconcile two apparently conflicting conclusions in the scholarly work examining this backlash? The question comes down to the particular interplay of these factors. I argue that the most promising approach may lie in tweaking our ideas about the relevant group that individuals use to make assessments about general welfare and the role of political entrepreneurs in manipulating these relevant groups. This, in turn, might explain why right-wing political parties appear to consistently gain from the ongoing backlash. I end with a consideration of the policy means that governments have to curb the political effects of economic grievances, and what explains the success or failure of such efforts. An economic recipe for backlash suggests the existence of an antidote.
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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; both teacher heads agree on what is shown here.
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".