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Record W6976712507 · doi:10.6068/dp1710f1ea82127

TREND: Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Health - Health Expenditures | Country: Australia, Austria, Belgium, Brazil, Canada, Chile, China, Czech Republic, Poland, South Korea, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States | Socioeconomic Indicator: Life Expectancy at Birth: Total, 1970 - 2011. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 062-001-035 Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Health - Life Expectancy | Country: Australia, Austria, Belgium, Brazil, Canada, Chile, China, Czech Republic, Poland, South Korea, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States | Socioeconomic Indicator: Life Expectancy at Birth: Total, 1970 - 2011. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 062-001-037

2020· other· en· W6976712507 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLife expectancyHealth carePublic healthGross domestic productConsumption (sociology)Social determinants of healthHealth indicatorGoods and servicesInvestment (military)

Abstract

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Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Health - Health Expenditures | Country: Australia, Austria, Belgium, Brazil, Canada, Chile, China, Czech Republic, Poland, South Korea, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States | Socioeconomic Indicator: Life Expectancy at Birth: Total, 1970 - 2011. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 062-001-035 Dataset: Presents the total public and private expenditures on health as a percentage of gross domestic product (GDP). Total expenditure on health care measures the final consumption of health goods and services plus capital investment in health care infrastructure. It includes spending by both public and private sources (including households) on medical goods and services, on public health and prevention programs, and on administration. 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: Health and Vital Statistics, International Relations and Trade Subject: Private Sector, Health Care Expenditures, Public Sector, Gross Domestic Product, Organization for Economic Cooperation and Development Countries (OECD) 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 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, 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 score0.172
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0030.000
Science and technology studies0.0060.002
Scholarly communication0.0060.006
Open science0.0050.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1870.014

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 head0.028
GPT teacher head0.273
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; 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
Published2020
Admission routes1
Has abstractyes

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