The Shadow Labor Supply and Its Implications for the Unemployment Rate
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
In the wake of the Great Recession, with more Americans unemployed than at any other time in the last quarter-century, millions of workers stopped seeking work. The crisis saw a sharp rise in the number of people who, in response to surveys, indicated they wanted a job but were not actively seeking one. As long as these individuals are not actively seeking work, they are not considered part of the labor force and are not counted as unemployed in official government statistics such as the unemployment rate. The group continued to swell through the first few years of the economic recovery and, by early 2013, numbered some 6.7 million—nearly 2 million more than before the crisis. Residing on the periphery of the labor market, this group may be viewed as a “shadow labor supply.” How these people fare in the months and years to come could have an important influence on the unemployment rate. If many of these people start actively seeking jobs as the economy recovers, they
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it