U.S. productivity grew at strong 2.9 percent rate in Q2
Bibliographic record
Abstract
U.S. productivity grew at an annual rate of 2.9 percent in the second quarter, the fastest pace in more than three years, while labor costs actually fell. U.S. productivity grew at an annual rate of 2.9 percent in the second quarter, which is the fastest pace in more than three years.The Labor Department says the April-June increase in productivity followed a much weaker 0.3 percent rate of gain in the first quarter.It was the strongest advance since a 3.1 percent gain in the first quarter of 2015.Labor costs actually fell at a 0.9 percent rate in the second quarter, the weakest showing in nearly four years.Productivity, a key factor determining how fast the economy can grow and how much living standards can increase, has been anemic throughout this expansion.The strong second quarter gain is expected to be a temporary blip rather than a lasting improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.031 |
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; both teacher heads agree on what is shown here.
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".