Où en sommes-nous dans la conception d’indicateurs de développement durable en transport ?
Bibliographic record
Abstract
Alors que l’urgence de l’opérationnalisation du développement durable dans le secteur des transports se fait sentir, les décideurs québécois ont besoin d’outils pour évaluer le progrès et les effets de leurs actions en termes de mobilité durable. Certes, il existe des indicateurs permettant de mesurer l’évolution de la mobilité des personnes, particulièrement pour l’automobile et le transport en commun. Cependant, aucun consensus sur un cadre d’évaluation de la mobilité durable n’existe, tant en ce qui a trait à la sélection qu’aux méthodes d’estimation d’indicateurs mesurant les impacts environnementaux, sociaux et économiques. Cet article présente la mobilité durable dans le contexte québécois, plusieurs enjeux liés aux indicateurs de mobilité durable, ainsi qu’un survol des données disponibles à Montréal et de leur contribution potentielle à l’estimation d’indicateurs de mobilité durable.
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".