The Canada‐U.S. Free Trade Agreement and labour market adjustment in Canada
Bibliographic record
Abstract
Evidence suggests that the Canada‐U.S. Free Trade Agreement (CUSTA) had almost no effect on earnings and had a small negative effect on manufacturing employment. Theory suggests that a change in trade policy may affect skilled and less‐skilled workers differently. The labour market consequences of CUSTA tariff reductions are analysed in this paper. It is found that the tariff reductions lowered employment predominantly among less‐skilled workers but did not affect the earnings of either skilled or less‐skilled workers. The employment effects are due to the fact that relatively less‐skill‐intensive industries were more highly protected than high‐skill‐intensive industries prior to CUSTA. On montre que l'accord de libre échange Canada‐US n'a eu presque pas d'effet sur les gains et un impact négatif faible sur l'emploi dans le secteur manufacturier. La théorie suggère qu'un changement dans la politique commerciale peut avoir un effet différent sur les travailleurs qualifiés et moins qualifiés. Le mémoire analyse les effets des réductions dans les droits de douane sur le marché du travail. Il appert que les réductions des tarifs douaniers ont eu des effets négatifs sur l'emploi des moins qualifiés mais n'ont pas affecté le niveau des gains des qualifiés et des moins qualifiés. Les effets d'emploi sont attribuables au fait que les industries engageant des personnes relativement moins qualifiées étaient davantage protégés avant l'accord de libre échange que les industries employant une main d'oeuvre plus qualifiée.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".