U.S. productivity grew at weak 0.4 percent rate in Q1
Bibliographic record
Abstract
U.S. productivity grew at an annual rate of just 0.4 percent in the first quarter, even weaker than initially estimated, while labor costs rose at a bit faster pace. U.S. productivity grew at an annual rate of just 0.4 percent in the first quarter, which was even weaker than initially estimated.The Labor Department says the January-March productivity increase was revised down from the 0.7 percent gain initially estimated a month ago. The rise in productivity was only marginally better than the 0.3 percent increase in the fourth quarter but below the 2.6 percent third quarter increase.Labor costs rose 2.9 percent, up from an initial estimate of a 2.7 percent gain in the first quarter. Productivity, which is a key factor determining how fast the economy can grow and how much living standards can increase, has been anemic throughout the economic recovery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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; 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".