Senate Democratic Policy Committee Hearing “Are We Exporting American Jobs?”
Bibliographic record
Abstract
States Chamber of Commerce, the world’s largest business federation representing more than three million members and organizations of every size, sector, and region. We appreciate the opportunity to appear before you today to discuss the U.S. economy, the jobless recovery, and state of our manufacturing sector. The Current Economic Environment and the Jobless Recovery Although, the U.S. economy emerged from the last recession in November 2001, real economic growth remained lackluster advancing at less than a 3 percent pace for four quarters. Beginning in the second quarter of this year, however, the economy began to accelerate. Real GDP growth was 3.3 percent in the second quarter and a remarkable 7.2 percent in the third quarter of this year. At the same time, economic growth has become more balanced with business fixed investment growing more than 11 percent at an annual rate in the third quarter, and investment in equipment and software advancing at a 15.4 percent annual pace over the same period. With the inventory-to-sales ratio at a record low level, a likelihood that the dollar will depreciate further, an expectation of somewhat lower oil prices, and the emergence of stronger than expected growth abroad, the prospects for economic growth in the near term look very good.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.026 | 0.016 |
| Insufficient payload (model declined to judge) | 0.067 | 0.038 |
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".