Trend 1996 - 2005. Statistics Canada. CANSIM: Culture and Leisure - Trade in Culture Goods and Services | Country: Canada | Table: Film, video and audio-visual production, by type of producer | Variable: Conventional and pay television producers, Television productions 75 minutes or more | Units: #, 1996-2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-055.
Bibliographic record
Abstract
Statistics Canada (2015). CANSIM: Culture and Leisure - Trade in Culture Goods and Services | Country: Canada | Table: Film, video and audio-visual production, by type of producer | Variable: Conventional and pay television producers, Television productions 75 minutes or more | Units: #, 1996-2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 075-001-055. Dataset: Provides statistics on trade in culture goods and services in Canada. Culture goods include books, magazines, newspapers, postcards, calendars, films, videos, DVDs, sheet music, compact discs, cassettes, vinyl LPs, paintings (original and reproductions), photographs, sculptures, ornaments and figurines, architectural plans, designs and drawings, advertising materials, museum exhibits, coin and stamp collections, and antiques. Culture services include copyrights, trademarks, performances, broadcasts, design services, and services of performing artists, authors, composers, or sculptors. Unrecorded media, such as blank CDs, are excluded, as is equipment used to consume, display, play, or enhance culture goods, eg, DVD players, stereos, televisions, and portrait frames. 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 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: Leisure Activities, Culture, Commerce
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".