Industrial Production and Capacity Utilization: The 2002 Historical and Annual Revision
Bibliographic record
Abstract
In late 2002, the Board of Governors of the Federal Reserve System published a revision to its index of industrial production and the related measures of capacity utilization. The primary feature of the revision was the reclassification back to 1972 of production and capacity indexes for individual industries from the Standard Industrial Classification System to the North American Industry Classification System. The revision also reflects the incorporation of newly available, more comprehensive source data, and it introduced improved methods for measuring the annual real output of communications equipment manufacturing. Along with the updating and the restatement of the data using the North American Industry Classification System, all production and capacity indexes are now expressed as percentages of output in 1997. The new information resulted in an upward revision to the rate of increase in industrial production and capacity from 1997 to 2000. For that period, the average rate of industrial capacity utilization is 0.7 percentage point higher than previously reported. The most recent business-cycle peak is still June 2000, at 116.2 percent of 1997, with the low being the fourth quarter of 2001. The rate of industrial capacity in the third quarter of 2002, at 76.2 percent, is essentially unchanged from previously reported data. The rate is more than 5 percentage points below its 1972-2001 average and about 3 percentage points below the trough in the 1990-91 recession but 5 percentage points above the trough in the 1982 recession.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".