Evaluation of Alternative Measures of Size for Sampling of Establishments in the NCS October
Bibliographic record
Abstract
The National Compensation Survey, conducted by the Bureau of Labor Statistics, is an establishment survey sampled yearly from a national frame using probability proportionate to establishment employment size. The national frame is developed from administrative files maintained quarterly by the States for the Unemployment Insurance program. Each establishment on the frame is assigned a measure of employment size equal to the employment in the third month of the frame quarter. In 2011, approximately 15% of the establishments in the frame, which includes seasonal businesses, reported an employment of zero, an employment that must be adjusted to ensure that the establishment has a chance of selection. In the past, establishments with zero employment have been assigned an employment equal to one employee, with some cases resulting in large weights for the occupations selected from these companies. The large weights lead to an over-representation of these occupations in the sample. This paper presents alternative measures of size values and discusses the options for best determining the measure of size for all establishments in the frame.
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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 | 0.411 | 0.628 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.010 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".