Tableau de bord pour suivre l'évolution de l'économie de Montréal en lien avec la Stratégie de développement économique
Bibliographic record
Abstract
Suite a la mise en place de la Strategie de developpement economique 2018-2022, le CIRANO a ete mandate pour developper un tableau de bord afin de suivre l’evolution et la performance de l’economie de Montreal. L’objectif du tableau de bord est de fournir une reddition de compte annuellement pour permettre le suivi de la Strategie de developpement economique de la Ville de Montreal. En s’appuyant sur une methodologie developpee au CIRANO pour comparer les regions economiques canadiennes, des grandes villes internationales comparables a Montreal, ont ete identifiees. L’analyse a ainsi pu etre realisee a deux niveaux, soit (1) avec les grandes villes canadiennes et (2) avec cinq grandes villes internationales. Le tableau de bord propose un total de 43 indicateurs, incluant 18 indicateurs de niveau « macro » et 25 indicateurs de niveau « meso » se rapportant aux objectifs lies aux grandes orientations de la Strategie de developpement economique de la Ville de Montreal. Ce rapport est confidentiel.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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".