Bibliographic record
Abstract
The Free Trade @ 10 conference, organized by the McGill Institute for the Study of Canada, was a unique event in that it brought the people who made the history together with academics, business and labour leaders who assessed the impact of the Canada-United States Free Trade Agreement (fta) and the North American Free Trade Agreement (nafta).The tenth anniversary of fta implementation and the fifth anniversary of the nafta provided an opportunity to examine the results of free trade, to appraise its impact and to look at the road ahead.In Montreal over two days in June, 1999, several hundred participants, including dozens of students from universities from all three nafta countries, did just that.This book, Free Trade: Risks and Rewards, is the record of the proceedings of the Free Trade @ 10 conference.The 10-year Canada-U.S. trade data and five-year trade flows among the three nafta countries indicate a dramatic increase in bilateral and trilateral trade over the period.In 1988, the last year before fta implementation, Canada's merchandise exports to the U.S. were $101 billion.In 1998, merchandise exports totaled $271 billion, and while these are constant dollars, the inflation rate over the period was remarkably low.Over the first 10 years of free trade, Canadian merchandise exports to the U.S. increased by nearly 170%.Similarly U.S. merchandise exports to Canada of $86 billion in 1988 rose to $203 billion in 1998, an increase of nearly 150%.Trade in services also more than doubled during the period, to Canadian imports of $32 billion and exports of $27 billion.Altogether, two-way trade in merchandise and services is now about $1.5 billion a day.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.567 | 0.408 |
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".