Survey of Professional forecasters 2023
Bibliographic record
Abstract
Forecasters Maintain Their Expectations for Growth in 2023 The forecasters see the U.S. economy in 2023 expanding at the same pace as they predicted three months ago, according to 38 panelists surveyed by the Federal Reserve Bank of Philadelphia. The forecasters predict annual-average over annualaverage growth in real GDP of 1.3 percent in 2023, unrevised from their estimate of three months ago. The panelists are also maintaining their forecast for growth in the second quarter at an annual rate of 1.0 percent, unchanged compared with their previous projection. However, while their predictions for the second quarter and for 2023 remain the same, the forecasters revised upward their predictions for the third quarter of 2023. They also revised downward their fourth-quarter estimates.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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".