Most Recent Data (2005). Statistics Canada. CANSIM: Seniors - Income, Pensions and Wealth | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of plants with research and development services that were supplied from different locations | Variable: From province or territory, Petroleum and coal products manufacturing, Plants that bought or did not buy research and development services, Non-innovative plants | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-185.
Bibliographic record
Abstract
Statistics Canada (2015). CANSIM: Seniors - Income, Pensions and Wealth | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of plants with research and development services that were supplied from different locations | Variable: From province or territory, Petroleum and coal products manufacturing, Plants that bought or did not buy research and development services, Non-innovative plants | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 075-001-185. Dataset: Reports statistics on the amounts and types of income, eg, earnings, investment income, retirement income, other income, and government transfers, received by Canadian seniors, as well as the number and percentage of seniors in low income. Persistence of low income among seniors and transitions of seniors into and out of low income are also covered. Assets, debts, and net worth (wealth) of seniors are also included.\ CANSIM is Statistics Canada's key socioeconomic database. The datasets included here provide statistics on the Canadian population, and the nation’s resources, economy, society, and culture. In addition to conducting a Census every five years, approximately 350 active surveys are conducted on virtually all aspects of Canadian life. Statistics are provided for the nation as a whole, provinces, and other subnational geographies where available. Category: Population and Income Source: Statistics Canada Established as Canada's central statistical office by the Statistics Act of 1985, Statistics Canada is required to "collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and conditions of the people of Canada." Its main objectives are to provide statistical information and analysis about Canada’s economic and social structure and to promote sound statistical standards and practices. http://www.statcan.gc.ca/ Subject: Population Aging, Older Adults, Pensions, Social Insurance Systems, Poverty, Wealth, Earnings, Income
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".