Trend 2013/2 - 2016/1. Organisation for Economic Co-operation and Development (OECD). Main Economic Indicators: Labor Market Statistics | Country: Spain | Indicator: Employment rate, Aged 15-64, Males - Level, rate or quantity series, s.a., 2013/2-2016/1. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 062-002-012.
Bibliographic record
Abstract
Organisation for Economic Co-operation and Development (OECD) (2016). Main Economic Indicators: Labor Market Statistics | Country: Spain | Indicator: Employment rate, Aged 15-64, Males - Level, rate or quantity series, s.a., 2013/2-2016/1. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 062-002-012. Dataset: This subset of the Main Economic Indicators (MEI) database includes data on unit labor cost, hourly earnings, labor force, registered unemployment and job vacancies. The Organisation for Economic Co-operation and Development (OECD) Main Economic Indicators database provides comparative statistics on OECD member countries and other non-member countries. Data availability varies by nation and by time period. See the technical documentation for information on national practices related to the compilation of data. Category: Labor and Employment, International Relations and Trade 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/ Subject: Employer Costs, Job Openings, Labor Force, Earnings, Wages, Unemployment
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.172 | 0.106 |
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; both teacher heads agree on what is shown here.
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".