Trend 2000 - 2006. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, barriers to electronic commerce, by North American Industry Classification System (NAICS) | Variable: Users of the Internet that do not buy, Miscellaneous wholesaler-distributors, Customers are not ready | Units: %, 2000-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-125.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Statistics Canada (2015). CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, barriers to electronic commerce, by North American Industry Classification System (NAICS) | Variable: Users of the Internet that do not buy, Miscellaneous wholesaler-distributors, Customers are not ready | Units: %, 2000-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 075-001-125. Dataset: Presents statistics on the penetration of e-commerce and the use of information and communications technologies by Canadian businesses and government. Information and communications technology (ICT) represents a long list of goods and services, including older technologies, such as the telephone and television, and more recent ones, such as mobile phones and the Internet. 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: Industry, Business, and Commerce, Government and Politics 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: Telecommunications Services, Businesses, State Government, Information and Communications Technology, Federal Government, Electronic Commerce
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it