Just Released: Benchmark Revisions Paint a Brighter Picture of (Most of) the Regional Economy
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
Every March, the Bureau of Labor Statistics releases benchmark revisions of state and local payroll employment for the preceding two years. While employment data are released monthly for all 50 states and many metropolitan areas, the monthly figures are estimated based on a sample of firms. The annual revisions are based on an almost complete count of workers (now available up through mid-2014) from the records of the unemployment insurance system and re-estimated data for the remainder of the year. In this post, we briefly summarize the mixed but mostly stronger performance in the region in 2014 indicated by these employment revisions. We highlight the most pronounced changes across our District—highlighted by New York City’s even stronger-looking boom—using the percentage change in total employment from the fourth quarter of 2013 to the fourth quarter of 2014 as the metric.
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 | 0.000 | 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 it