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Enregistrement 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 sur OpenAlexaboutno aff

Notice bibliographique

RevueData Planet · 2016
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNonfarm payrollsEarningsMetropolitan areaClosing (real estate)PopulationQuarter (Canadian coin)Sample (material)Current Population Survey

Résumé

récupéré en direct d'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/

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,180
Score d'incertitude au seuil0,359

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,013
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0040,014
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0030,002
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0990,110

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,276
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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