Most Recent Data (06/2013). Statistics Canada. CANSIM: Business Performance and Ownership - Small and Medium-Sized Businesses | Country: Canada | Table: 551-0004 | Table Name: Canadian business patterns, location counts, employment size and North American Industry Classification System (NAICS), national industries | Variable: Plastic pipe and pipe fitting manufacturing-Total, all sizes-# | Units: #, 06/2013. Data Planet™ Statistical Ready Reference: A SAGE Publishing Resource Dataset-ID: 075-001-023.
Bibliographic record
Abstract
Statistics Canada (2018). CANSIM: Business Performance and Ownership - Small and Medium-Sized Businesses | Country: Canada | Table: 551-0004 | Table Name: Canadian business patterns, location counts, employment size and North American Industry Classification System (NAICS), national industries | Variable: Plastic pipe and pipe fitting manufacturing-Total, all sizes-# | Units: #, 06/2013. Data Planet™ Statistical Ready Reference: A SAGE Publishing Resource [Dataset]. Dataset-ID: 075-001-023. Dataset: Provides statistics on characteristics and financing activities of small and medium-sized businesses in Canada, including balance sheets and investment activities, sources of financing, credit amounts authorized, credit amounts outstanding, and types of financing instruments, and other measures of the economic importance of small firms. 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. NOTE: Per Statistics Canada, the data download files available for the CANSIM database do not include information on hierarchical relationships among data values; ie, it is not possible to determine what subtotal values for a variable are included in a total value. The absence of this information renders the exported data values meaningless. For this reason, Data-Planet has archived the dataset. Category: Industry, Business, and Commerce 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: Small Businesses, Financials
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".