Reflections on the Struggle Against the Canada-US Free Trade Agreement (TFA), 30 Years Later
Bibliographic record
Abstract
The implementation of the Canada-US Free Trade Agreement (CUSFTA) in January 1989 marked a decisive moment in the rise of neoliberalism as a political project in Canada. While the left, and socialist political economists in particular, played a central role in galvanizing the agreement and contributed in no small part to the demise of the Conservative government in 1993, the free trade agenda continued to move forward through the 1990s. This Special Issue revisits the history of struggles against free trade in Canada with two aims in mind: first to remember the coalitions through which opposition was organized, the mobilization of socialist critiques by activists and intellectuals, and the key events leading up to the adoption of the agreement. Second, drawing from this history to make sense of how things have changed over the past 30 years, as right-wing nationalists have increasingly taken the lead in opposing free trade, while neoliberals have sought to rebrand their project as ‘progressive’. How can those on the left effectively confront the project of free trade today while at the same time challenging both far-right nationalism and neoliberal globalization?
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.052 | 0.028 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".