Résultats de scénarios à l’aide d’un modèle à moyen terme de l’économie du Québec
Bibliographic record
Abstract
In this medium term model of the Quebec economy, output in the various sectors of the economy is determined by demand. The different components of final demand take into account the volume exports of Quebec output to the rest of Canada and to the United States. Employment in the various sectors of the economy is determined by the inverse of production function whereas output is distributed among the different economic agents. Income influences final demand. Prices and wages are in part determined endogenously whereas the labour supply, government expenditures, tax rates are treated exogenously in the forecasting period. The results are generally good and various forecasts are made for the 1978-85 period. Three sets of assumptions define what is called a weak, medium and strong scenario. In all scenarios, we observe a productivity slowdown. If we assume the current trend in the slowdown of the public sector is maintained, employment growth is largely explained by the growth of private sector of the economy. Then, it turns out that in all forecasts, employment growth will allow any significant reduction of the unemployment rate over the forecasting period. Only a major shift in productivity trend which would allow Quebec to take a larger share of the North American market could improve the labour market in the years to come.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".