Low-Income-Country Import Competition and the Structure of Earnings Inequality in Canada, 1996–2001
Bibliographic record
Abstract
This paper uses a detailed employer–employee dataset to test the effects of low-income-country import competition on the earnings of workers in manufacturing industries in Canada. From 1996 to 2001 earnings inequality increased: the wage gap between manufacturing workers with a university degree and those without a high school diploma rose from 35% to 43%. Greater import competition is found to explain part of the growing wage gap, consistent with Stolper–Samuelson effects. Point estimates suggest that these effects increased slightly over the period of study and are strongest in Quebec, Ontario, and British Columbia, provinces with the highest low-income-country import-penetration rates. However, the results also suggest (i) the relative wage effects of increased import competition are not as ‘clear cut’ as predicted by the Stolper–Samuelson theorem and (ii) that other individual and plant-level factors are important determinants of the structure of earnings inequality in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".