Bibliographic record
Abstract
United States strives to force the Chinese into agreement of increasing the value of their exchange rate to help the USA avoid inflation As China did not come into an agreement with the USA, Tariffs are being put on Chinese products entering USA. However China as began to add tariff on poultry received from the US as well. China was previously not named in the legislation permitting US to add tariff on their goods. But recently a bill was passed giving the commerce department the ability to place important tariffs on all countries to undervalue their currency. The bill passed in legislation had the support of 99 republicans. China has been managing their currency in a manner that makes their goods cheaper to sell and American goods more expensive. The Chinese manipulation of their currency has been quite expensive for the USA, as it has cost them $1.5 billion jobs increasing the percentage of unemployment greatly and significantly. This imposition of tariffs on Chinese goods could result in effecting $300 billion dollars worth of their products. It is obvious that the Americans are attempting to improve and acknowledge their growth and power. As predictions have developed over this conflict, arguing the fact that China will not negotiate with the USA at this point rather fight back and also approach in adding tariffs on US imports. However, this reaction by the Chinese will only worsen the scenario and result in the possible inflation of the US economy or worldwide trade war. This is a very sensitive time for the United States as their biggest hopes are dependent on the Chinese. But it doesn’t look like they will be too satisfied with the outcome.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.048 | 0.006 |
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".