Bibliographic record
Abstract
The KORUS FTA was signed on June 30, 2007, but has not yet been sent to Congress for ratification. US concerns about auto and beef trade are the main stumbling blocks. At the Toronto G-20 Summit in June 2010, Presidents Obama and Lee Myung Bak tasked their officials to find solutions by the November Seoul G-20 Summit. If a deal is struck, implementing legislation could be submitted to Congress in early 2011. This paper assesses the problems and potential solutions to these problems and options for legislative action. The author concludes that, once submitted, the KORUS FTA will be approved for three reasons--all related to actions taken by other countries that could adversely affect US commercial and security interests in the Asia-Pacific region. The first reason is to demonstrate support for a strong ally facing North Korean aggression. Neither country wants to let a few provisions in a major trade agreement create friction in a strategically important bilateral alliance. The second reason is to secure a level playing field for US exporters in the Korean market. The imminent signing of the Korea-EU FTA, an agreement modeled on and largely comparable to the KORUS FTA, increases the urgency of Congressional action on the KORUS FTA since US and EU exports compete for sales in the Korean market. The third reason relates to the ability of US officials to advance US economic interests through an effective trade policy. Implementing KORUS is important to help maintain the credibility of US trade initiatives that seek to boost US exports, constrain Chinese economic influence in the Asia-Pacific region, and advance overall US foreign policy and security interests.
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 | 0.032 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".