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Record W4414414233 · doi:10.1177/20531680251379914

The source of economic shocks matters for their political outcomes

2025· article· en· W4414414233 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch & Politics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsMcGill University
Fundersnot available
KeywordsOffshoringPoliticsAuthoritarianismEconomic impact analysisRecessionProductivityOpportunity cost

Abstract

fetched live from OpenAlex

Do different economic shocks favor different types of political leadership? Using a survey experiment conducted on 3500 American respondents, we offer causal evidence for an unexpected relation between different types of economic shocks and a demand for a radical political response. First, we show that individuals believe politicians have a role in preventing layoffs due to both offshoring and automation, compared to run-of-the-mill bankruptcies. Second, we find strong evidence that economic shocks due to offshoring lead to greater demands for leaders who display authoritarian traits, with no equivalent effect for layoffs due to automation. When presented with news of an offshoring event, respondents favor leaders who claim to be more willing to flout the rule of law, to implement divisive policies, and to employ force. By contrast, traits commonly associated with populism, such as siding with “the people” or preferring political outsiders, see no association with either offshoring or automation shocks. Our findings support the view that some economic shocks provide a greater opportunity for political candidates willing to turn to radical political solutions.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.469
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it