Supply and Use Tables, 2010-2021, Level L61 [Canada]
Bibliographic record
Abstract
The supply and use tables focus on measuring the productive structure of the economy. They trace production of products by domestic industries, combined with imports, through their use as intermediate inputs or as final consumption, investment or exports. The system provides a measure of value added by industry—total output less intermediate inputs. These tables can be used to calculate economy-wide gross domestic product (GDP) either directly, by summing value added over the industries, or indirectly, by summing to the economy-wide cost of primary inputs (income-based GDP) or by computing the grand total of the flow of commodities into final demand categories (expenditure-based GDP). With the 2015 comprehensive revision, the Canadian System of Macroeconomic Accounts (CSMA) has introduced a major presentational change to the national and the provincial and territorial input-output tables. The previous CSMA input-output presentation differed from the international standard and the practice found in most national statistical organizations. The CSMA has aligned its presentation with the international standard and replaces the presentation found in catalogues 15F0041X and 15F0042X, as well as 15F0002X. (Replaces the "interprovincial and international trade flows", "national input output tables", and "provincial input output tables")
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.028 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.089 | 0.048 |
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 source (direct Gemma or distilled Codex), 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".