Gender-Identity Protection, Trade, and the Trump Administration: A Tale of Reluctant Progressivism
Bibliographic record
Abstract
The Trump Administration has been hostile to transgender people, stripping away many protections from discrimination established by the prior administration. It is therefore striking that President Trump’s signature international agreement to date—the “new NAFTA” recently negotiated with Canada and Mexico—includes a provision requiring all three countries to implement appropriate policies to protect workers against discrimination based on gender identity. This provision has a similar requirement with respect to discrimination on the basis of sexual orientation, notwithstanding the fact that the Trump Administration’s domestic policies have also shown hostility to such protections. How did this provision come to be included in the trade agreement? How powerful is it in practice? And what lessons does its inclusion have for international trade law more generally? Drawing on subtle changes in the wording of the initial and revised texts of the trade agreement, this Essay hypothesizes that the initial inclusion of gender-identity and sexual-orientation protections took place with little to no interagency consultation with the Department of Justice, which has taken a strong position against such workplace protections. Once these protections made it into the initial public draft, the Trump Administration could—and did—water down the protections in subsequent negotiations, but the Administration could not remove the protections entirely. The net effect is an international commitment to the protection of gender identity and sexual orientation that is substantively weak but still meaningful—and that carries considerable expressive force. The inclusion of the protections shows that trade agreements can lead even powerful governments to make value-laden commitments at odds with their own domestic agendas.
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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 | 0.024 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.090 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.014 | 0.035 |
| Insufficient payload (model declined to judge) | 0.003 | 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".