Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Contraiy to most reports, the economy is recovering, albeit slowly. It would be a mistake to act on the assumption that we are facing a deep recession or the start of another great depression. In retrospect, the recession will be seen as relatively mild. Our current unemployment rate at 6.8% of the labor force is below the rates in many countries including Britain (8.7%), Canada (10.3%), France (9.7%) or Italy (10%). Germany has had a boom for several years, but its unemployment rate at 6.3% is only slightly below ours. Economic forecasts are often wide of the mark. We should not add to our current problems by basing policy action on forecasts about the speed of the recovery. The best forecasts of economic growth have an average error about equal to the average rate of growth. A comprehensive study of forecast errors shows that forecasters cannot distinguish on average between booms and recessions next year or even next quarter. Basing policy actions on forecasts is likely to produce errors of timing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it