Perceived technological threat and vote choice: evidence from 15 European democracies
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
The political consequences of workplace technological adoption have become a focus of recent party politics research. This article contributes to this literature by directly examining how the perceived threat of technological change relates to support for populist and non-populist left and right parties. It does so in two ways: first, by examining subjective rather than objective automation exposure, and second by distinguishing between personal and collective threat perceptions. Using vote choice data from 15 European countries, this article shows that subjective perception of personal automation exposure relates to increased support for left parties and decreased support for populist-right parties, while concern over collective risk relates to increased support for the populist right. These patterns suggest that fear of workplace technological change elicits both material and status concerns. The article concludes with counterfactual analyses demonstrating that both non-populist and populist left-wing parties could benefit by mobilizing voters who feel personally threatened by automation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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