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.
Bibliographic record
Abstract
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
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.015 |
| 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) | 0.088 | 0.112 |
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".