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Record W6981117075

Développement d'un modèle d'agent pour étudier l'influence du comportement citoyen et de l'attitude environnementale sur la gestion durable des matières résiduelles

2024· other· fr· W6981117075 on OpenAlexaboutno aff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2024
Typeother
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Public managementEnvironmental policy
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: La gestion des déchets urbains est devenue une préoccupation majeure, en raison des défis croissants liés à la durabilité environnementale et à la gestion efficace des ressources. Dans de nombreuses régions, y compris au Québec, la quantité de déchets générés par les ménages continue d'augmenter, mettant une pression accrue sur les systèmes de gestion des déchets et entraînant des conséquences néfastes pour l'environnement et la santé publique. Face à cette réalité, les municipalités cherchent à mettre en œuvre des stratégies innovantes pour réduire la quantité de déchets envoyés en décharge, promouvoir le recyclage et encourager le tri à la source. Cependant, la conception de politiques efficaces dans ce domaine nécessite une compréhension approfondie des comportements des citoyens, des facteurs qui influent sur ces comportements et de l'impact des décisions municipales sur l'ensemble du système de gestion des déchets. C'est dans ce contexte que cette thèse prend tout son sens. Elle vise à combler ces lacunes en développant un outil d'aide à la décision qui permet d'évaluer l'impact des décisions stratégiques des municipalités sur les performances sociales et environnementales des systèmes de gestion des déchets. En se concentrant sur le comportement de tri à la source des citoyens, cette recherche cherche à fournir aux décideurs municipaux des informations précieuses pour concevoir et mettre en œuvre des politiques de gestion des déchets plus efficaces et durables. Pour atteindre cet objectif, plusieurs objectifs spécifiques ont été définis. Tout d'abord, cette recherche vise à développer un cadre méthodologique pour prédire la génération de déchets solides par les citoyens, en prenant en compte divers facteurs tels que la démographie, le contexte socioéconomique et la localisation géographique. Il s'agit de comprendre comment ces différents facteurs influent sur la quantité de déchets générés, afin de mieux anticiper les besoins en gestion des déchets à l'échelle locale. Un deuxième objectif est de modéliser le comportement de tri à la source des citoyens en fonction de leur attitude environnementale, en utilisant un modèle à base d'agents. Cette modélisation permettra de comprendre comment les attitudes individuelles influencent les pratiques de tri des ménages, et comment ces pratiques impactent la qualité des flux de matières recyclables. ABSTRACT: Urban waste management has become a major concern due to growing challenges related to environmental sustainability and efficient resource management. In many regions, including Quebec, the quantity of waste generated by households continues to increase, placing increased pressure on waste management systems and resulting in adverse consequences for the environment and public health. In response to this reality, municipalities are seeking to implement innovative strategies to reduce the amount of waste sent to landfills, promote recycling, and encourage source separation. However, designing effective policies in this domain requires a deep understanding of citizen behaviors, the factors influencing these behaviors, and the impact of municipal decisions on the entire waste management system. It is within this context that this thesis holds significance. Its aim is to address these gaps by developing a decision support tool that evaluates the impact of municipal strategic decisions on the social and environmental performance of waste management systems. Focusing on citizens' source separation behavior, this research seeks to provide valuable information to municipal decision-makers to design and implement more effective and sustainable waste management policies. To achieve this goal, several specific objectives have been defined. Firstly, this research aims to develop a methodological framework to predict the generation of solid waste by citizens, taking into account various factors such as demographics, socioeconomic context, and geographical location. Secondly, the objective is to model citizens' source separation behavior based on their environmental attitudes, using an agent-based model. Finally, the thesis aims to establish a link between citizens' source separation behavior and the rest of the waste management system, to simulate the impacts of municipal decisions on the overall efficiency of the system. This includes assessing how modulation of source separation through municipal strategic decisions can affect the quality of recycled materials, CO2 emissions associated with waste collection and treatment, and other aspects of social and environmental sustainability of the system.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0180.002

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.

Opus teacher head0.011
GPT teacher head0.233
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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