Bibliographic record
Abstract
The past several years have been tumultuous ones for U.S. trade policy. After strident rhetoric from Donald Trump during his presidential campaign, his administration followed up with a wide range of aggressive actions. Congress, U.S. trading partners, businesses, and consumers have all been pushed to their limits by an administration that has taken U.S. policy in a protectionist and unilateral direction. If Democratic presidential candidate Joe Biden wins the 2020 election, he will face the challenge of developing a coherent U.S. trade policy that provides stability and certainty. This paper presents an overview of the trade issues a President Joe Biden would likely face, with some suggestions on possible approaches his administration might take. It covers seven major topics, with some overlap among them: Trade agreements: What should U.S. trade agreements say, and with whom should the United States negotiate them? The World Trade Organization (WTO): How should a Biden administration deal with the many challenges faced by the multilateral trade institution that is the foundation of the trading system? China: How should a Biden administration approach China’s controversial and difficult integration into the trading system? The United States‐Mexico‐Canada Agreement (USMCA): Can some of the USMCA’s flaws be fixed during implementation? Executive trade actions: How should a Biden administration use executive branch discretion over trade policy? The role of Congress: Is it time to recalibrate the legislative/executive balance of power over trade? Personnel: Who should be in charge of U.S. trade policy?
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".