Canadian Business Patterns, December 2012 [B2020]
Bibliographic record
Abstract
The Canadian Business Patterns contains data that reflects counts of business locations (as of December 2008) and business establishments (prior to December 2009) by: 9 employment size ranges, including "indeterminate" (as of December 1997); geography groupings: province/territory, census division, census subdivision (before December 2008), census metropolitan area and census agglomeration; and industry using the North American Industry Classification System (tables at the 2, 3, 4 and 6-digit level) as of December 1998. Before December 2004, these data were also presented using the Standard Industrial Classification (tables at the 1, 2, 3 and 4-digit level). The data published in the Canadian Business Patterns represents the current number of locations or establishments for a specific reference period which is taken from the Business Register Central Frame Data Base. It is not intended for use as a time series because changes that affect the continuity of the data might resu lt from changes in methodology. Some examples are: the change to another version of the Standard Geographical Classification (SGC) or the North American Industry Classification System (NAICS), the addition of the new territory of Nunavut and new rules to better identify inactive units.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.011 |
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".