Définir et mesurer la multimodalité de l'offre de transport
Bibliographic record
Abstract
RÉSUMÉ: « La multimodalité est un concept qui peut décrire l’offre, la demande et les politiques de transport. Une offre multimodale désigne un système de transport proposant plusieurs options de modes de transport. Une demande multimodale décrit des individus utilisant divers modes de transport. Les politiques de transport multimodales sont des mesures qui visent à augmenter ces deux types de multimodalité. La multimodalité prend une importance croissante dans le domaine du transport pour diverses raisons, principalement celle de l’attention portée à la diminution de la dépendance à l’automobile privée, au profit du transport en commun et des modes actifs et partagés. L’augmentation de la multimodalité présente de nombreux avantages environnementaux et sociaux, et permet également d’améliorer les systèmes de transport eux-mêmes, en augmentant leur résilience, sécurité et vitesse entre autres. Pour mettre en oeuvre des stratégies visant à accroître la multimodalité, il est essentiel de pouvoir la définir et la quantifier afin de mesurer son évolution. Plusieurs indicateurs de mesure de la demande ont été établis, testés et appliqués dans la littérature. En revanche, peu d’articles se concentrent sur la mesure de la multimodalité de l’offre de transport et ceux qui existent prennent en compte principalement la présence et l’accessibilité des infrastructures, sans considérer le niveau de service de ces différents modes. L’objectif de cette étude est donc de développer un indicateur permettant de mesurer la multimodalité de l’offre de transport qui tient compte de la qualité de service des modes et qui soit adapté au contexte montréalais. Ce mémoire propose une méthodologie pour évaluer la multimodalité de l’offre de transport par zone, en se basant sur des indicateurs établis pour chaque mode. Pour chaque mode, trois éléments sont pris en compte : la disponibilité du mode dans la zone, l’accessibilité au mode au sein de la zone, et la qualité de service du mode dans la zone. Ensuite, les zones étudiées sont classifiées selon ces indicateurs, et les groupes sont comparés pour établir un classement des groupes selon leur multimodalité.» ABSTRACT: « Multimodality is a concept that can describe transport supply, demand and policies. Multimodal supply refers to a transport system offering several transport mode options while multimodal demand describes individuals using different modes of transport. And multimodal transport policies are measures aimed at increasing both types of multimodality. Multimodality is becoming increasingly important in the transportation field for a variety of reasons, especially the focus on reducing dependence on the private automobile, in favor of public transit as well as active and shared modes. Increasing multimodality has many environmental and social benefits. It also improves the transport systems themselves, by increasing their resilience, safety and speed among other things. To implement strategies aimed at increasing multimodality, it is essential to be able to define and quantify it in order to measure its evolution. Several indicators for measuring the multimodality of the transport demand have been established, tested and applied. However, few studies focus on measuring the multimodality of the transport supply, and those that do mainly take into account the availability and accessibility of the infrastructures, without considering the level of service of these different modes. The aim of this study is therefore to develop an indicator for measuring the multimodality of the transportation supply that takes into account the quality of service of the different modes, and that is adapted to the Montreal context. This thesis develops a methodology for assessing the multimodality of the transport supply by zone, based on indicators established for each mode. For each mode, three elements are considered: the availability of the mode in the area, the accessibility of the mode within the area, and the quality of service of the mode in the area. The zones are then grouped according to these indicators, and the groups are compared to establish a ranking of the groups according to their multimodality.»
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".