Bibliographic record
Abstract
Risks and RewardsFew public policy issues have stirred political passions on both sides of the Canada/US border as free trade did in the late 1980s.Negotiated between Canada and the United States in 1987, the Free Trade Agreement became the dominant issue in the November 1988 Canadian federal election, perhaps the most dramatic and divisive campaign in the second half of the twentieth century.Ten years after implementation of the agreement, the McGill Institute for the Study of Canada organized a major conference to renew the discussion of free trade and consider its economic impact.It also marked the fifth anniversary of the North American Free Trade Agreement by expanding the discussion to include the impact of nafta on Mexico, as well as the nafta side agreement of the environment.Free Trade provides a historical framework for ongoing discussion of economic and environmental issues.While there is empirical evidence on trade flows -they increased dramatically in both directions -the debate on related issues continues.The impact of free trade on jobs and manufacturing productivity, the effectiveness of dispute settlement, the growth of foreign direct investment, the absence of adjustment programs, and the consequences for social programs are all issues for spirited discussion.Free Trade: Risks and Rewards is an important reminder of why the issue was so passionately debated at the time and why it remains important.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.880 | 0.787 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".