Threats for workers or opportunities for consumers? The impact of the Great Recession on perceived trade threat in 21 countries
Bibliographic record
Abstract
Two competing perspectives have been offered to explain how the Great Recession (GR) impacted citizens’ perspectives on international trade. The citizens-as-workers perspective maintains that anti-trade attitudes increase during economic downturns because higher imports of foreign products pose a severe threat to workers’ job security, whereas the citizens-as-consumers perspective suggests that favorable attitudes toward international trade increase as imports provide better opportunities for cheaper consumer goods. In this article, we examine how the dual identities of citizens—as workers and consumers—play a role in shaping how the GR affects perceived trade threat. Using multilevel ordered logit models, we analyze responses from 19,982 respondents nested within 21 countries in the 2013 International Social Survey Program survey. We find that the GR exacerbated perceived trade threat. We also find that the GR intensified pro-trade attitudes in countries with fast-growing unemployment. The results suggest that anti-trade sentiments of citizens-as-workers were dominant after the GR, but pro-trade sentiments of citizens-as-consumers were also present as a countervailing force against a protectionist backlash.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".