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Record W6939355145 · doi:10.6068/dp154c9277fd54

TREND: (PWC) Bureau of Labor Statistics. State and Metro Area Employment, Hours, and Earnings: All Employees | State: New Hampshire | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Total Private, Computer and Electronic Product Manufacturing, Information, Finance and Insurance, Educational Services, Health Care and Social Assistance, 01/1990 - 11/2015. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 002-030-001

2016· other· en· W6939355145 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNonfarm payrollsEarningsMetropolitan areaClosing (real estate)PopulationQuarter (Canadian coin)Sample (material)Current Population Survey

Abstract

fetched live from OpenAlex

(PWC) Bureau of Labor Statistics. State and Metro Area Employment, Hours, and Earnings: All Employees | State: New Hampshire | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Total Private, Computer and Electronic Product Manufacturing, Information, Finance and Insurance, Educational Services, Health Care and Social Assistance, 01/1990 - 11/2015. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 002-030-001 Dataset: Presents estimates of the number of employees on nonfarm payrolls by major industry for the 50 United States, Washington, DC, Puerto Rico, and the Virgin Islands, and by metropolitan statistical area (MSA), defined by the US Office of Management and Budget as having at least one urbanized area of 50,000 or more inhabitants. Seasonally adjusted and nonadjusted estimates are reported. Seasonally adjusted estimates eliminate the influence of such seasonal events as changes in weather, reduced or expanded production, harvests, major holidays, and the opening and closing of schools. These adjustments make it easier to observe the cyclical and other nonseasonal movements in the series. Employment data are seasonally adjusted with a procedure called X-12-ARIMA. http://download.bls.gov/pub/time.series/sm/, Hours, and Earnings data are collected as part of the Current Employment Statistics (CES) program of the Bureau of Labor Statistics (BLS), which is a federal-state cooperative endeavor. As part of the CES, each month BLS collects data on employment, hours, and earnings from a sample of about 486,000 nonfarm establishments that employ nearly 40 percent of the total nonfarm population in the 50 United States, Washington, DC, Puerto Rico, and the Virgin Islands. All establishments with 1,000 employees or more are asked to participate in the survey along with a representative sample of smaller establishments. Sample respondents extract the requested data from their payroll records, which must be maintained for a variety of tax and accounting purposes. Establishments reporting on the schedule are classified into industries using the 2002 North American Industry Classification System (NAICS) Manual, based on their principal product or activity determined from information on annual sales volume. For an establishment making more than one product, the entire employment is included under the industry of the principal product or activity. Data submitted on the schedules are used by BLS analysts in developing statewide and metropolitan area estimates. Employment is the total number of persons on establishment payrolls employed full or part time who received pay for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any workers who are on paid sick leave, on paid holiday, or who work during only part of the specified pay period. Persons on the payroll of more than one establishment are counted in each establishment. Data exclude proprietors, self-employed, unpaid family or volunteer workers, farm workers, and domestic workers. Persons on layoff the entire pay period, on leave without pay, on strike for the entire period or who have not yet reported for work are not counted as employed. Government employment covers only civilian workers. ftp://ftp.bls.gov/pub/time.series/sm/ Category: Labor and Employment Subject: Workers, Private Sector, Businesses, Employment, Civilian Employment, Metropolitan Areas, Industry Source: Bureau of Labor Statistics The Bureau of Labor Statistics (BLS) of the United States Department of Labor is the principal fact-finding agency for the federal government in the broad field of labor economics and statistics. The BLS is an independent national statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the US Congress, other federal agencies, state and local governments, business, and labor. The BLS also serves as a statistical resource to the Department of Labor. http://www.bls.gov/

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.180
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.014
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0990.110

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.

Opus teacher head0.013
GPT teacher head0.276
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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