RANKING: US Census Bureau, United States Census Bureau. County Business Patterns by NAICS Code (2003 - Current): Industrial Establishments - First Qtr Payroll | NAICS Code: 4842 | NAICS Description: Specialized Freight Trucking, 2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-007-002
Bibliographic record
Abstract
US Census Bureau, United States Census Bureau. County Business Patterns by NAICS Code (2003 - Current): Industrial Establishments - First Qtr Payroll | NAICS Code: 4842 | NAICS Description: Specialized Freight Trucking, 2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-007-002 Dataset: Shows business payroll at first quarter of the reference year. First quarter payroll includes all forms of compensation, such as salaries, wages, commissions, bonuses, vacation allowances, sick-leave pay, and the value of payments inkind (e.g., free meals and lodgings) paid during the 1st quarter (January to March) to all employees. Data are from the US Census Bureau's County Business Patterns (CBP), an annual series that provides national and subnational data on the distribution of economic data by size and industry. Presented here are data by state and county. CBP covers most of the country's economic activity. CBP basic data items are extracted from the Business Register, a file of all known single and multi-establishment employer companies maintained and updated by the Census Bureau. The annual Company Organization Survey provides individual establishment data for multi-establishment companies. Data for single-establishment companies are obtained from various Census Bureau programs, such as the Annual Survey of Manufactures and Current Business Surveys, as well as from administrative records of the Internal Revenue Service, the Social Security Administration, and the Bureau of Labor Statistics. The series excludes data on self-employed individuals, employees of private households, railroad employees, agricultural production employees, and most government employees. Statistics were tabulated by industry as defined in North American Industry Classification System (NAICS). CBP covers most NAICS industries, excluding crop and animal production (NAICS 111,112); rail transportation (NAICS 482); Postal Service (NAICS 491); pension, health, welfare, and vacation funds (NAICS 525110, 525120, 525190); trusts, estates, and agency accounts (NAICS 525920); private households (NAICS 814); and public administration (NAICS 92). The dataset incorporates code changes for the reference year. https://www-census-gov.libproxy2.usc.edu/programs-surveys/cbp/data/datasets.html Category: Industry, Business, and Commerce, Labor and Employment Subject: Employer Costs, Payroll, Compensation, Businesses, Wages, Salaries Source: United States Census Bureau The US Census Bureau is a bureau of the US Department of Commerce. The major functions of the Census Bureau are authorized by Article 2, Section 2 of the United States Constitution, which provides that a census of population shall be taken every 10 years, and by Title 13 and Title 26 of the United States Code of Federal Regulations. The Census Bureau is responsible for numerous statistical programs, including census and surveys of households, governments, manufacturing and industries, and for US foreign trade statistics. The first US census was conducted in 1790 for the purposes of apportioning state representation in the US House of Representatives and for the apportionment of taxes. https://www-census-gov.libproxy2.usc.edu
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.
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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.025 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.158 | 0.211 |
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".