Arthur Hjorth
Biographic Data
| ID | 7709788 |
|---|---|
| NAME | Arthur Hjorth |
| GIVEN NAMES | Arthur |
| FAMILY NAME | Hjorth |
| SIGNATURE | HJORTH A |
| AFFILIATIONS | Aarhus University |
| ORCID | 0000-0001-8652-0354 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The shift to plant-rich diets in Denmark
Leveraging Modularity During Replication of High-Fidelity Models
High-fidelity models are increasingly used to predict, and guide decision making. Prior work has emphasized the importance of replication in ensuring reliable modeling, and has yielded important replication strategies. However, this work is based on relatively simple theory generating models, and its lessons might not translate to high-fidelity models used for decision support. Using NetLogo we replicate a recently published high-fidelity model e…
LevelSpace
Multi-Level Agent-Based Modeling (ML-ABM) has been receiving increasing attention in recent years. In this paper we present LevelSpace, an extension that allows modelers to easily build ML-ABMs in the popular and widely used NetLogo language. We present the LevelSpace framework and its associated programming primitives. Based on three common use-cases of ML-ABM coupling of heterogenous models, dynamic adaptation of detail, and cross-level interac…
Implementation Research Methodologies for Achieving Scientific Equity and Health Equity
Implementation science has great potential to improve the health of communities and individuals who are not achieving health equity. However, implementation science can exacerbate health disparities if its use is biased toward entities that already have the highest capacities for delivering evidence-based interventions. In this article, we examine several methodologic approaches for conducting implementation research to advance equity both in our…
No prominent works on this page.
Implementation Research Methodologies for Achieving Scientific Equity and Health Equity
Implementation science has great potential to improve the health of communities and individuals who are not achieving health equity. However, implementation science can exacerbate health disparities if its use is biased toward entities that already have the highest capacities for delivering evidence-based interventions. In this article, we examine several methodologic approaches for conducting implementation research to advance equity both in our…
Leveraging Modularity During Replication of High-Fidelity Models
High-fidelity models are increasingly used to predict, and guide decision making. Prior work has emphasized the importance of replication in ensuring reliable modeling, and has yielded important replication strategies. However, this work is based on relatively simple theory generating models, and its lessons might not translate to high-fidelity models used for decision support. Using NetLogo we replicate a recently published high-fidelity model e…
LevelSpace
Multi-Level Agent-Based Modeling (ML-ABM) has been receiving increasing attention in recent years. In this paper we present LevelSpace, an extension that allows modelers to easily build ML-ABMs in the popular and widely used NetLogo language. We present the LevelSpace framework and its associated programming primitives. Based on three common use-cases of ML-ABM coupling of heterogenous models, dynamic adaptation of detail, and cross-level interac…
The shift to plant-rich diets in Denmark
Artificial Intelligence (2 works) · Computer Science (2 works) · NetLogo (2 works) · Programming language (2 works) · Psychology (2 works) · Adaptation (eye (1 work) · Adolescent Sexual and Reproductive Health (1 work) · Agent-based model (1 work) · Biology (1 work) · Business (1 work)