Bibliographic record
Abstract
HE NATIONAL income and product accounts (NIPAs) of the Bureau of Economic Analysis (BEA) include two alternative measures of economic output: gross domestic product (GDP) and gross do mestic income (GDI). GDP is an expenditure-based measure and is estimated based on spending on final goods and services. GDI is an income-based measure and is estimated based on income generated in the production of goods and services. Before the recession that began in the fourth quarter of 2007 and ended in the second quarter of 2009, GDI growth was generally lower than GDP growth, which has generated discus sion about whether the source data and adjustments that underlie GDP reflect enough economic cyclicality. This article explores an alternative: whether the source data and adjustments that underlie GDI reflect too much economic cyclicality and whether this effect may explain a significant share of the difference between GDP and GDI during the downturn. In particular, this article identifies and explains the following four factors that require adjustments to convert financial- or tax
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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 | 0.049 | 0.251 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".