Bibliographic record
Abstract
The CANDIDE model has been used by the Economic Council to examine Canada's economic potential, to analyze the effects of economic forces, and to consider the appropriateness of alternative policies in reaching economic objectives. For its Annual Reviews, the model provides an analytical basis for taking into account the interdependence of a number of phenomena, including those related to demographic trends, external economic conditions and domestic policies influencing supply and demand, and thus facilitates estimation of the potential development of the economy over the longer term. Within this context, a realizable set of medium-term objectives can then be established. These have been presented by the Council as performance indicators for the three years immediately ahead and they are subsequently used to monitor and assess economic developments. The model also is used by the Council to examine how various economic influences work their way through the Canadian economy. In its Annual Reviews, for example, the effects of alternative scenarios for energy investment and prices have been considered. In a special study of the construction industry, the model was used to trace the causes and effects of instability in this sector. Some illustrative results from each of these impact studies are provided. The model has also been employed to explore the implications of certain past and future changes in commercial policy, including separating out the impact of the Canada-United States Automobile Agreement, and in examining changes that have been taking place in labour markets. Each of these areas have been the subject of special studies carried out by the Council.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".