Intra‐industry Trade Liberalization: Why Skilled Workers are More Likely to Support Free Trade
Bibliographic record
Abstract
Abstract This paper presents a theoretical model and empirical analysis that connects the prevalence of intra‐industry trade with increased wage inequality from trade liberalization in both skilled and unskilled labor abundant countries. The Stolper–Samuelson effect is incorporated into an intra‐industry trade liberalization (intra‐ITL) hypothesis where skilled labor opposes protectionism in all countries engaged in intra‐industry trade because skilled workers gain at the expense of unskilled workers from multilateral trade liberalization within the skill‐intensive sector. We examine empirical evidence on whether skilled individuals are more supportive of trade liberalization than unskilled individuals across 31 countries with different levels of intra‐industry trade and skill endowments. We find that the extent to which countries engage in intra‐industry trade in high‐tech commodities is strongly linked with the intensity of opposition to protection by skilled labor. Regression results strongly support our hypothesis that skilled workers, almost everywhere, are more likely to support free trade.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".