A "Fair" Trade Law of Nations or A "Fair" Global Law of Economic Relations?
Bibliographic record
Abstract
This essay examines the dispute between advocates of free trade and those who support fair trade (the “fair” trade debate). This debate is explored in the context of globalization. The author argues that globalization has created, and continues to create, a new global identity and global social relationships that make “justice” both possible and necessary. Such relationships have fundamental implications for thenature of global social policy, particularly international law and international trade law. The author asserts that the fair trade debate presupposes two independent contending foes: “me” versus “you,” and “mine” versus “theirs.” He argues, however, that globalization has shifted the dialogue to one of “us” and “ours.” Consequently, shared institutions are employed to determine what is best for this shared social space and disputing parties contribute to the creation and definition of this social space. The softwood lumber dispute is used to illustrate the author’s argument in that though parties to the dispute pursue their own private agendas and public mandates, they are also creating and defining a new trans-border community. As such, the dispute does not concern ensuring trade law is “fair” for the United States or “fair” for Canada; rather, the aim is a fair settlement for an emerging trans-boundary community.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".