The main goal of the project is to understand how the development of local community sports associations work and change over time. The project is divided into three different stages:
- Scraping and gathering local sports association data to create a structure that is directly linkable to register data.
- Combining data gathered on local sports associations with Danish register data.
- Explore how to use sports association data combined with register data over time to understand how changes in local community affects and changes the composition of sports association participation.
Using machine learning models allows us to fully structure and map data over time and allows us to create predictive models to better understand how local community and sports associations are linked and if there are any direct causal mechanisms that can either limit or further participation. Thus, the project will develop exploratory methodologies that allows for structuring and modeling of data as well as methodologies for prediction.
Participants
- Sociology
- Health
- DGI