Measuring Resource Utilization in the Labor Market
Bibliographic record
Abstract
In the U.S. labor market unemployed individuals that are actively looking for work are more than three times as likely to become employed as those individuals that are not actively looking for work and are considered to be out of the labor force (OLF). Yet, on average, every month twice as many people make the transition from OLF to employment than do from unemployment to employment. These observations on labor market transitions suggest that the standard unemployment rate and its extensions proposed by the Bureau of Labor Statistics are both too coarse and too narrow as measures of resource utilization in the labor market. These measures are too narrow since they exclude a large part of the population that is potentially employable, and they are too coarse since they assume the same labor force attachment for all nonemployed individuals. We construct a measure of resource utilization in the labor market, a nonemployment index, that is both comprehensive and accounts for differences in labor force attachment. Prior to 2007, the standard unemployment rate was highly correlated with our nonemployment index but, during the recession of 2007--09 and its aftermath, the standard unemployment rate overstated the extent of underutilization in the labor market.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".