Impact of the 2015 U.S. Dollar Rise on Export Prices and on the Agricultural Industry
Bibliographic record
Abstract
U.S. export prices experienced a major decline in 2015, as evidenced by the Bureau of Labor Statistics (BLS) export price index. Prices for U.S. exports, published in dollar terms, decreased 6.6 percent in 2015, the largest calendar-year decline since the index was first published in 1983. However, the large decline in the U.S. dollar export price index did not tell the entire story. When measured in foreign currency terms, export prices were actually higher because of the strong dollar. The value of the dollar strengthened against the euro, Japanese yen, Chinese yuan, and Canadian dollar. Continued slow global economic and trade growth dampened demand for U.S. exports and influenced U.S. export price trends. The meeting of the strong dollar and lackluster demand for U.S. exports was particularly challenging for the U.S. agricultural industry. This Beyond the Numbers article analyzes what impact the strengthening dollar had on certain agricultural commodities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".