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Record W6920344892 · doi:10.6068/dp15e0093d78e17

Trend 1973 - 2011. Bureau of Labor Statistics. International Labor Statistics [Archive]: Manufacturing Labor Productivity and Unit Labor Costs | Country: Taiwan | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: MANUFACTURING AGGREGATE HOURS INDEX, 1973-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-031-005.

2017· other· en· W6920344892 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2017
Typeother
Languageen
FieldHealth Professions
TopicHealth, Technology, Consumer Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsUnit (ring theory)ProductivityCurrencyLabor costLiberian dollarCompensation of employeesAggregate dataIndex (typography)National accounts

Abstract

fetched live from OpenAlex

Bureau of Labor Statistics (2017). International Labor Statistics [Archive]: Manufacturing Labor Productivity and Unit Labor Costs | Country: Taiwan | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: MANUFACTURING AGGREGATE HOURS INDEX, 1973-2011. 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

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0060.004
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0100.001

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 head0.059
GPT teacher head0.362
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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