Withdrawing the United States from the WTO Government Procurement Agreement (GPA): Assessing Potential Damage to the U.S. and Its Contracting Community
Bibliographic record
Abstract
The Trump administration is mulling an executive order that would trigger U.S. withdrawal from the WTO Agreement on Government Procurement (GPA), according to reports from Bloomberg and POLITICO. Withdrawal from the GPA would deprive U.S. suppliers of a key point of access to public procurement markets internationally, under a world-wide agreement which has set global standards and opened over a trillion dollars annually in business opportunities. See, e.g., Anderson et al., “Assessing the Value of Future Accessions to the WTO Agreement on Government Procurement (GPA): Some New Data Sources, Provisional Estimates, and An Evaluative Framework for Individual WTO Members Considering Accession,” 2012 Pub. Proc. Law Rev. 113. The United States could forfeit access to important public procurement markets in Canada and many other countries, and the United States could lose its leadership role (which dates back to World War II) in shaping global standards in public procurement, even as more countries are joining the GPA.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| 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".