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Enregistrement W6976553964 · doi:10.6068/dp15e0091523a28

Trend 1950 - 2011. Bureau of Labor Statistics. International Labor Statistics [Archive]: Manufacturing Labor Productivity and Unit Labor Costs | Country: Norway | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: REAL HOURLY COMPENSATION, CPI BASIS, PRODUCTIVITY SERIES, 1950-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-031-005.

2017· other· en· W6976553964 sur OpenAlexaboutno aff

Notice bibliographique

RevueData Planet · 2017
Typeother
Langueen
DomaineEngineering
ThématiqueEngineering and Materials Science Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésUnit (ring theory)ProductivityCurrencyLiberian dollarLabor costNational accountsNational Income and Product AccountsCompensation of employeesIndex (typography)Aggregate data

Résumé

récupéré en direct d'OpenAlex

Bureau of Labor Statistics (2017). International Labor Statistics [Archive]: Manufacturing Labor Productivity and Unit Labor Costs | Country: Norway | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: REAL HOURLY COMPENSATION, CPI BASIS, PRODUCTIVITY SERIES, 1950-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 002-031-005. Dataset: Provides data on labor productivity, defined as real output per hour worked, and unit labor costs, defined as the cost of labor input required to produce one unit of output, for the United States and other nations. The indexes are constructed from three basic aggregate measures: total real output, hours worked, and nominal compensation. Indexes for unit labor costs are prepared on a national currency basis; currency exchange rates are used to prepare indexes for unit labor costs on a US dollar basis. In general, the measures relate to total manufacturing as defined by the International Standard Industrial Classification (ISIC). Data for the United States are in accordance with the North American Industry Classification System (NAICS), except for compensation data before 1987, which are based on SIC 1987. Canadian data are in accordance with NAICS 1997, starting with 1961 data. The US data are based on the system of national income and product accounts (NIPA). For other countries, the data for the most recent years are based on the United Nations System of National Accounts 1993; data for earlier years are based on previously used systems. For most of the economies, the output measures are real value added in manufacturing, based on national accounts. Note that the US manufacturing output series used for international comparisons differs from the series that the Bureau of Labor Statistics publishes as part of its major-sector productivity and costs measures in that a value-added output (vs a sectoral output) basis is used as the better concept for international comparisons of labor productivity. The United States Bureau of Labor Statistics (BLS) International Labor Comparisons (ILC) program publishes statistical series of data adjusted to common concepts to facilitate statistical analyses of the economic and labor market performance of the US relative to other economies and to evaluate the competitive position of the US. The emphasis of the current program is on the development of international comparisons of the labor force, employment, unemployment, and related indicators; hourly compensation costs of employees and production workers; productivity and unit labor costs in manufacturing; real gross domestic product per capita and per employed person; and consumer prices. The measures compiled relate primarily to the major developed countries, but other countries or areas of importance to US foreign trade are included in some measures. All data on nations other than the US are drawn from secondary sources; BLS does not initiate surveys or data collection programs abroad. Data are obtained from (a) statistical agencies of other countries; (b) international and supranational bodies such as the United Nations, the International Labor Office (ILO), the Organization for Economic Cooperation and Development (OECD), and the Statistical Office of the European Communities (EUROSTAT); and (c) private agencies such as banks, industry associations, and research institutions. In order to achieve the budget cuts required by the Balanced Budget and Emergency Deficit Control Act and protect core programs, the Bureau of Labor Statistics eliminated the International Labor Comparisons program in 2013. Category: Labor and Employment, International Relations and Trade 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/ Subject: Employer Costs, Production Workers, Manufacturing Industry, Labor Productivity

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)0,002
score de la tête « metaresearch » (Gemma)0,015
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 enseignants0,153
Score d'incertitude au seuil0,304

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,015
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0040,015
Études des sciences et des technologies0,0010,000
Communication savante0,0030,003
Science ouverte0,0030,002
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0880,112

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 Opus0,024
Tête enseignante GPT0,261
Écart entre enseignants0,237 · 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
Publié2017
Routes d'admission1
Résumé présentoui

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