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Record W6920663359 · doi:10.6068/dp1593b5ed3ec78

TREND: (IMF) Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Household Income and Wealth - Household Disposable Income | Country: Australia | Socioeconomic Indicator: Real Household Disposable Income, 2000 - 2012. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 062-001-068

2016· other· en· W6920663359 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHousehold incomeConsumption (sociology)Socioeconomic statusTotal personal incomeSocial securityPersonal incomeStatisticEquity (law)Net national incomeEarnings

Abstract

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(IMF) Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Household Income and Wealth - Household Disposable Income | Country: Australia | Socioeconomic Indicator: Real Household Disposable Income, 2000 - 2012. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 062-001-068 Dataset: Reports the annual percentage growth in household disposable income a statistic defined as "real" vs nominal. Household disposable income is the sum of household final consumption expenditure and savings (minus the change in net equity of households in pension funds). It also corresponds to the sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions paid by employees, the self-employed and the unemployed. The indicator for the household sector includes the disposable income of nonprofit institutions serving households (NPISH). The price deflator used to obtain real values is consistent with that used to deflate the final consumption expenditure of households and NPISH. This dataset provides indicators included in the OECD Factbook 2014: Economic, Environmental, and Social Statistics, updated annually by the Organisation for Economic Co-operation and Development (OECD). Indicators, reported in 12 broad subject areas, cover a wide range of topics: agriculture, economic production, education, energy, environment, foreign aid, health, industry, information and communications, international trade, labor force, population, taxation, public expenditure, and research and development. Data are provided for all OECD member countries and Brazil, China, India, Indonesia, Russia, and South Africa, where available. NOTE: The data presented here are copyrighted by OECD and reproduction is subject to OECD permissions policies: See http://www.oecd.org/rights for further information. Indicator descriptions are based on the OECD Factbook 2014. http://stats.oecd.org/BrandedView.aspx?oecd_bv_id=factbook-data-en&doi=data-00590-en Category: Population and Income, International Relations and Trade Subject: Economic Development, Household Income, Standard of Living Source: Organisation for Economic Co-operation and Development (OECD) Established in 1961, when 18 European countries plus the United States and Canada joined together to create an organization dedicated to global development, the Organisation for Economic Co-operation and Development (OECD) today includes 34 member countries from around the globe, ranging from North and South America to Europe and the Asia-Pacific region. Member countries include many of the world’s advanced countries as well as emerging nations. The OECD mission remains the promotion of policies that will improve the economic and social well-being of people around the world. The OECD collects and analyzes data on a broad range of topics to help governments foster prosperity and fight poverty through economic growth and financial stability, at the same time taking the environmental implications of economic and social development into account. The OECD Secretariat collects and analyzes data, after which committees discuss policy regarding this information, the Council makes decisions, and then governments implement recommendations. The performance of individual countries is monitored following implementation via a system of multilateral surveillance and a peer review process. The OECD is headquartered in Paris, France, and it is funded by its member countries. National contributions are based on a formula that takes account of the size of each member's economy. The largest contributor is the United States, which provides nearly 24% of the budget, followed by Japan. http://www.oecd.org/

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 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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.936
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.012
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0640.100

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 head0.024
GPT teacher head0.268
Teacher spread0.245 · 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.

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
Published2016
Admission routes1
Has abstractyes

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